{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T10:19:17Z","timestamp":1788171557872,"version":"build-2803163510"},"reference-count":204,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62173345"],"award-info":[{"award-number":["62173345"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007129","name":"Natural Science Foundation of Shandong Province","doi-asserted-by":"publisher","award":["ZR2023LZH017"],"award-info":[{"award-number":["ZR2023LZH017"]}],"id":[{"id":"10.13039\/501100007129","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int. J. Mach. Learn. &amp; Cyber."],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1007\/s13042-026-03218-x","type":"journal-article","created":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T11:18:19Z","timestamp":1783941499000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Application of artificial intelligence in unmanned aerial vehicles: a survey"],"prefix":"10.1007","volume":"17","author":[{"given":"Qing","family":"Zhu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengyao","family":"Xi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ning","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peiying","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Konstantin Igorevich","family":"Kostromitin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"issue":"2","key":"3218_CR1","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1109\/COMST.2015.2495297","volume":"18","author":"L Gupta","year":"2016","unstructured":"Gupta L, Jain R, Vaszkun G (2016) Survey of important issues in uav communication networks. IEEE Commun Surv Tutor 18(2):1123\u20131152. https:\/\/doi.org\/10.1109\/COMST.2015.2495297","journal-title":"IEEE Commun Surv Tutor"},{"issue":"4","key":"3218_CR2","doi-asserted-by":"publisher","first-page":"3038","DOI":"10.1109\/COMST.2023.3323344","volume":"25","author":"Y Bai","year":"2023","unstructured":"Bai Y, Zhao H, Zhang X, Chang Z, J\u00e4ntti R, Yang K (2023) Toward autonomous multi-uav wireless network: a survey of reinforcement learning-based approaches. IEEE Commun Surv Tutor 25(4):3038\u20133067. https:\/\/doi.org\/10.1109\/COMST.2023.3323344","journal-title":"IEEE Commun Surv Tutor"},{"issue":"11","key":"3218_CR3","doi-asserted-by":"publisher","first-page":"17038","DOI":"10.1109\/TITS.2024.3424525","volume":"25","author":"J Shan","year":"2024","unstructured":"Shan J, Jiang W, Huang Y, Yuan D, Liu Y (2024) Unmanned aerial vehicle (uav)-based pavement image stitching without occlusion, crack semantic segmentation, and quantification. IEEE Trans Intell Transp Syst 25(11):17038\u201317053. https:\/\/doi.org\/10.1109\/TITS.2024.3424525","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"3","key":"3218_CR4","doi-asserted-by":"publisher","first-page":"2334","DOI":"10.1109\/COMST.2019.2902862","volume":"21","author":"M Mozaffari","year":"2019","unstructured":"Mozaffari M, Saad W, Bennis M, Nam Y-H, Debbah M (2019) A tutorial on uavs for wireless networks: applications, challenges, and open problems. IEEE Commun Surv Tutor 21(3):2334\u20132360. https:\/\/doi.org\/10.1109\/COMST.2019.2902862","journal-title":"IEEE Commun Surv Tutor"},{"issue":"2","key":"3218_CR5","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1109\/MNET.131.2200477","volume":"38","author":"P Zhang","year":"2024","unstructured":"Zhang P, Chen N, Shen S, Yu S, Kumar N, Hsu C-H (2024) Ai-enabled space-air-ground integrated networks: management and optimization. IEEE Netw 38(2):186\u2013192. https:\/\/doi.org\/10.1109\/MNET.131.2200477","journal-title":"IEEE Netw"},{"issue":"1","key":"3218_CR6","doi-asserted-by":"publisher","first-page":"496","DOI":"10.1109\/COMST.2023.3312221","volume":"26","author":"H Kurunathan","year":"2024","unstructured":"Kurunathan H, Huang H, Li K, Ni W, Hossain E (2024) Machine learning-aided operations and communications of unmanned aerial vehicles: a contemporary survey. IEEE Commun Surv Tutor 26(1):496\u2013533. https:\/\/doi.org\/10.1109\/COMST.2023.3312221","journal-title":"IEEE Commun Surv Tutor"},{"key":"3218_CR7","doi-asserted-by":"publisher","unstructured":"Jiang Y, Li X, Zhu G, Li H, Deng J, Han K, Shen C, Shi Q, Zhang R (2025) Integrated sensing and communication for low altitude economy: opportunities and challenges. IEEE Commun Mag: 1\u20137. https:\/\/doi.org\/10.1109\/MCOM.001.2400685","DOI":"10.1109\/MCOM.001.2400685"},{"issue":"3","key":"3218_CR8","doi-asserted-by":"publisher","DOI":"10.3390\/s25030772","volume":"25","author":"C Chen","year":"2025","unstructured":"Chen C, Gao S, Pei H, Chen N, Shi L, Zhang P (2025) Novel surveillance view: a novel benchmark and view-optimized framework for pedestrian detection from uav perspectives. Sensors 25(3):722","journal-title":"Sensors"},{"issue":"2","key":"3218_CR9","doi-asserted-by":"publisher","first-page":"1395","DOI":"10.1109\/COMST.2024.3424533","volume":"27","author":"S Wu","year":"2025","unstructured":"Wu S, Chen N, Xiao A, Zhang P, Jiang C, Zhang W (2025) Ai-empowered virtual network embedding: a comprehensive survey. IEEE Commun Surv Tutor 27(2):1395\u20131426. https:\/\/doi.org\/10.1109\/COMST.2024.3424533","journal-title":"IEEE Commun Surv Tutor"},{"issue":"7","key":"3218_CR10","doi-asserted-by":"publisher","first-page":"6996","DOI":"10.1109\/TVT.2022.3168574","volume":"71","author":"G Niu","year":"2022","unstructured":"Niu G, Wu L, Gao Y, Pun M-O (2022) Unmanned aerial vehicle (uav)-assisted path planning for unmanned ground vehicles (ugvs) via disciplined convex-concave programming. IEEE Trans Veh Technol 71(7):6996\u20137007. https:\/\/doi.org\/10.1109\/TVT.2022.3168574","journal-title":"IEEE Trans Veh Technol"},{"issue":"1","key":"3218_CR11","doi-asserted-by":"publisher","first-page":"5344","DOI":"10.1002\/dac.5344","volume":"38","author":"K Zhan","year":"2025","unstructured":"Zhan K, Chen N, Kumar SVNS, Kibalya G, Zhang P, Zhang H (2025) Edge computing network resource allocation based on virtual network embedding. Int J Commun Syst 38(1):5344","journal-title":"Int J Commun Syst"},{"issue":"10","key":"3218_CR12","doi-asserted-by":"publisher","first-page":"16374","DOI":"10.1109\/TVT.2025.3572680","volume":"74","author":"Y Shi","year":"2025","unstructured":"Shi Y, Wang J, Yi C, Wang R, Chen B (2025) Proactive application deployment for mec: an adaptive optimization based on imperfect multi-dimensional prediction. IEEE Trans Veh Technol 74(10):16374\u201316390. https:\/\/doi.org\/10.1109\/TVT.2025.3572680","journal-title":"IEEE Trans Veh Technol"},{"issue":"4","key":"3218_CR13","doi-asserted-by":"publisher","first-page":"4981","DOI":"10.1109\/TVT.2022.3222907","volume":"72","author":"B Liu","year":"2023","unstructured":"Liu B, Liu C, Peng M (2023) Computation offloading and resource allocation in unmanned aerial vehicle networks. IEEE Trans Veh Technol 72(4):4981\u20134995. https:\/\/doi.org\/10.1109\/TVT.2022.3222907","journal-title":"IEEE Trans Veh Technol"},{"issue":"4","key":"3218_CR14","doi-asserted-by":"publisher","first-page":"2684","DOI":"10.1109\/COMST.2024.3395358","volume":"26","author":"P Cao","year":"2024","unstructured":"Cao P, Lei L, Cai S, Shen G, Liu X, Wang X, Zhang L, Zhou L, Guizani M (2024) Computational intelligence algorithms for uav swarm networking and collaboration: a comprehensive survey and future directions. IEEE Commun Surv Tutor 26(4):2684\u20132728. https:\/\/doi.org\/10.1109\/COMST.2024.3395358","journal-title":"IEEE Commun Surv Tutor"},{"issue":"12","key":"3218_CR15","doi-asserted-by":"publisher","first-page":"12262","DOI":"10.1109\/TMC.2024.3406607","volume":"23","author":"Y Yang","year":"2024","unstructured":"Yang Y, Shi Y, Yi C, Cai J, Kang J, Niyato D, Shen X (2024) Dynamic human digital twin deployment at the edge for task execution: a two-timescale accuracy-aware online optimization. IEEE Trans Mob Comput 23(12):12262\u201312279. https:\/\/doi.org\/10.1109\/TMC.2024.3406607","journal-title":"IEEE Trans Mob Comput"},{"issue":"4","key":"3218_CR16","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1109\/MNET.011.2000567","volume":"35","author":"B Shang","year":"2021","unstructured":"Shang B, Yi Y, Liu L (2021) Computing over space-air-ground integrated networks: challenges and opportunities. IEEE Netw 35(4):302\u2013309. https:\/\/doi.org\/10.1109\/MNET.011.2000567","journal-title":"IEEE Netw"},{"issue":"6","key":"3218_CR17","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1109\/MNET.2024.3368753","volume":"38","author":"S Wu","year":"2024","unstructured":"Wu S, Chen N, Xiao A, Jia H, Jiang C, Zhang P (2024) Ai-enabled deployment automation for 6g space-air-ground integrated networks: challenges, design, and outlook. IEEE Netw 38(6):219\u2013226. https:\/\/doi.org\/10.1109\/MNET.2024.3368753","journal-title":"IEEE Netw"},{"issue":"9","key":"3218_CR18","doi-asserted-by":"publisher","first-page":"9250","DOI":"10.1109\/TVT.2022.3178094","volume":"71","author":"Y Duan","year":"2022","unstructured":"Duan Y, Chen N, Shen S, Zhang P, Qu Y, Yu S (2022) Fdsa-stg: fully dynamic self-attention spatio-temporal graph networks for intelligent traffic flow prediction. IEEE Trans Veh Technol 71(9):9250\u20139260. https:\/\/doi.org\/10.1109\/TVT.2022.3178094","journal-title":"IEEE Trans Veh Technol"},{"key":"3218_CR19","doi-asserted-by":"publisher","first-page":"1015","DOI":"10.1109\/OJCOMS.2021.3075201","volume":"2","author":"M-A Lahmeri","year":"2021","unstructured":"Lahmeri M-A, Kishk MA, Alouini M-S (2021) Artificial intelligence for uav-enabled wireless networks: a survey. IEEE Open J Commun Soc 2:1015\u20131040. https:\/\/doi.org\/10.1109\/OJCOMS.2021.3075201","journal-title":"IEEE Open J Commun Soc"},{"issue":"7","key":"3218_CR20","doi-asserted-by":"publisher","first-page":"4757","DOI":"10.1109\/TITS.2020.3041746","volume":"22","author":"H Fatemidokht","year":"2021","unstructured":"Fatemidokht H, Rafsanjani MK, Gupta BB, Hsu C-H (2021) Efficient and secure routing protocol based on artificial intelligence algorithms with uav-assisted for vehicular ad hoc networks in intelligent transportation systems. IEEE Trans Intell Transp Syst 22(7):4757\u20134769. https:\/\/doi.org\/10.1109\/TITS.2020.3041746","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"3","key":"3218_CR21","doi-asserted-by":"publisher","first-page":"3146","DOI":"10.1109\/TCSS.2022.3216621","volume":"11","author":"Y Duan","year":"2024","unstructured":"Duan Y, Chen N, Bashir AK, Alshehri MD, Liu L, Zhang P, Yu K (2024) A web knowledge-driven multimodal retrieval method in computational social systems: unsupervised and robust graph convolutional hashing. IEEE Trans Comput Soc Syst 11(3):3146\u20133156. https:\/\/doi.org\/10.1109\/TCSS.2022.3216621","journal-title":"IEEE Trans Comput Soc Syst"},{"issue":"3","key":"3218_CR22","doi-asserted-by":"publisher","first-page":"3348","DOI":"10.1109\/TNSM.2022.3232414","volume":"20","author":"P Zhang","year":"2023","unstructured":"Zhang P, Li Y, Kumar N, Chen N, Hsu C-H, Barnawi A (2023) Distributed deep reinforcement learning assisted resource allocation algorithm for space-air-ground integrated networks. IEEE Trans Netw Serv Manage 20(3):3348\u20133358. https:\/\/doi.org\/10.1109\/TNSM.2022.3232414","journal-title":"IEEE Trans Netw Serv Manage"},{"issue":"10","key":"3218_CR23","doi-asserted-by":"publisher","first-page":"6793","DOI":"10.1109\/TWC.2023.3245621","volume":"22","author":"X Hou","year":"2023","unstructured":"Hou X, Wang J, Jiang C, Zhang X, Ren Y, Debbah M (2023) Uav-enabled covert federated learning. IEEE Trans Wireless Commun 22(10):6793\u20136809. https:\/\/doi.org\/10.1109\/TWC.2023.3245621","journal-title":"IEEE Trans Wireless Commun"},{"key":"3218_CR24","doi-asserted-by":"publisher","first-page":"3363","DOI":"10.1109\/TIFS.2023.3279587","volume":"18","author":"P Zhang","year":"2023","unstructured":"Zhang P, Chen N, Li S, Choo K-KR, Jiang C, Wu S (2023) Multi-domain virtual network embedding algorithm based on horizontal federated learning. IEEE Trans Inf Forensics Secur 18:3363\u20133375. https:\/\/doi.org\/10.1109\/TIFS.2023.3279587","journal-title":"IEEE Trans Inf Forensics Secur"},{"issue":"2","key":"3218_CR25","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1109\/TNSM.2022.3216326","volume":"20","author":"S Wang","year":"2023","unstructured":"Wang S, Hosseinalipour S, Gorlatova M, Brinton CG, Chiang M (2023) Uav-assisted online machine learning over multi-tiered networks: a hierarchical nested personalized federated learning approach. IEEE Trans Netw Serv Manage 20(2):1847\u20131865. https:\/\/doi.org\/10.1109\/TNSM.2022.3216326","journal-title":"IEEE Trans Netw Serv Manage"},{"issue":"1","key":"3218_CR26","doi-asserted-by":"publisher","first-page":"931","DOI":"10.1109\/TVT.2021.3129504","volume":"71","author":"Z Xia","year":"2022","unstructured":"Xia Z, Du J, Wang J, Jiang C, Ren Y, Li G, Han Z (2022) Multi-agent reinforcement learning aided intelligent uav swarm for target tracking. IEEE Trans Veh Technol 71(1):931\u2013945. https:\/\/doi.org\/10.1109\/TVT.2021.3129504","journal-title":"IEEE Trans Veh Technol"},{"issue":"1","key":"3218_CR27","doi-asserted-by":"publisher","first-page":"62","DOI":"10.3390\/pr10010062","volume":"10","author":"R Mesquita","year":"2021","unstructured":"Mesquita R, Gaspar PD (2021) A novel path planning optimization algorithm based on particle swarm optimization for uavs for bird monitoring and repelling. Processes 10(1):62","journal-title":"Processes"},{"issue":"3","key":"3218_CR28","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1109\/TWC.2022.3204794","volume":"22","author":"X Zhang","year":"2023","unstructured":"Zhang X, Zhao H, Wei J, Yan C, Xiong J, Liu X (2023) Cooperative trajectory design of multiple uav base stations with heterogeneous graph neural networks. IEEE Trans Wireless Commun 22(3):1495\u20131509. https:\/\/doi.org\/10.1109\/TWC.2022.3204794","journal-title":"IEEE Trans Wireless Commun"},{"key":"3218_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108676","volume":"128","author":"Y Duan","year":"2022","unstructured":"Duan Y, Chen N, Zhang P, Kumar N, Chang L, Wen W (2022) Ms2gah: multi-label semantic supervised graph attention hashing for robust cross-modal retrieval. Pattern Recogn 128:108676","journal-title":"Pattern Recogn"},{"issue":"16","key":"3218_CR30","doi-asserted-by":"publisher","first-page":"14438","DOI":"10.1109\/JIOT.2023.3268316","volume":"10","author":"N Cheng","year":"2023","unstructured":"Cheng N, Wu S, Wang X, Yin Z, Li C, Chen W, Chen F (2023) Ai for uav-assisted iot applications: a comprehensive review. IEEE Internet Things J 10(16):14438\u201314461. https:\/\/doi.org\/10.1109\/JIOT.2023.3268316","journal-title":"IEEE Internet Things J"},{"issue":"12","key":"3218_CR31","doi-asserted-by":"publisher","first-page":"13162","DOI":"10.1109\/TVT.2021.3118446","volume":"70","author":"Y Nie","year":"2021","unstructured":"Nie Y, Zhao J, Gao F, Yu FR (2021) Semi-distributed resource management in uav-aided mec systems: a multi-agent federated reinforcement learning approach. IEEE Trans Veh Technol 70(12):13162\u201313173. https:\/\/doi.org\/10.1109\/TVT.2021.3118446","journal-title":"IEEE Trans Veh Technol"},{"issue":"5","key":"3218_CR32","doi-asserted-by":"publisher","first-page":"3582","DOI":"10.1109\/TII.2021.3116132","volume":"18","author":"C Feng","year":"2022","unstructured":"Feng C, Liu B, Yu K, Goudos SK, Wan S (2022) Blockchain-empowered decentralized horizontal federated learning for 5g-enabled uavs. IEEE Trans Industr Inf 18(5):3582\u20133592. https:\/\/doi.org\/10.1109\/TII.2021.3116132","journal-title":"IEEE Trans Industr Inf"},{"key":"3218_CR33","doi-asserted-by":"publisher","first-page":"92048","DOI":"10.1109\/ACCESS.2022.3202956","volume":"10","author":"AO Hashesh","year":"2022","unstructured":"Hashesh AO, Hashima S, Zaki RM, Fouda MM, Hatano K, Eldien AST (2022) Ai-enabled uav communications: challenges and future directions. IEEE Access 10:92048\u201392066","journal-title":"IEEE Access"},{"key":"3218_CR34","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1023\/A:1016639210559","volume":"31","author":"H Choset","year":"2001","unstructured":"Choset H (2001) Coverage for robotics-a survey of recent results. Ann Math Artif Intell 31:113\u2013126","journal-title":"Ann Math Artif Intell"},{"issue":"2","key":"3218_CR35","doi-asserted-by":"publisher","first-page":"1503","DOI":"10.1109\/TWC.2023.3290005","volume":"23","author":"Y Shi","year":"2024","unstructured":"Shi Y, Yi C, Wang R, Wu Q, Chen B, Cai J (2024) Service migration or task rerouting: a two-timescale online resource optimization for mec. IEEE Trans Wireless Commun 23(2):1503\u20131519. https:\/\/doi.org\/10.1109\/TWC.2023.3290005","journal-title":"IEEE Trans Wireless Commun"},{"issue":"5","key":"3218_CR36","doi-asserted-by":"publisher","first-page":"990","DOI":"10.1007\/s13198-021-01186-9","volume":"12","author":"D Mandloi","year":"2021","unstructured":"Mandloi D, Arya R, Verma AK (2021) Unmanned aerial vehicle path planning based on a* algorithm and its variants in 3d environment. Int J Syst Assur Eng Manag 12(5):990\u20131000","journal-title":"Int J Syst Assur Eng Manag"},{"key":"3218_CR37","doi-asserted-by":"crossref","unstructured":"Ma N, Cao Y, Wang X, Wang Z, Sun H (2020) A fast path re-planning method for uav based on improved a* algorithm. In: 2020 3rd International Conference on Unmanned Systems (ICUS), pp. 462\u2013467. IEEE","DOI":"10.1109\/ICUS50048.2020.9274912"},{"issue":"12","key":"3218_CR38","doi-asserted-by":"publisher","first-page":"9591","DOI":"10.1109\/JIOT.2021.3128883","volume":"9","author":"A Mondal","year":"2021","unstructured":"Mondal A, Mishra D, Prasad G, Hossain A (2021) Joint optimization framework for minimization of device energy consumption in transmission rate constrained uav-assisted iot network. IEEE Internet Things J 9(12):9591\u20139607","journal-title":"IEEE Internet Things J"},{"issue":"8","key":"3218_CR39","doi-asserted-by":"publisher","first-page":"5185","DOI":"10.1109\/TWC.2022.3232366","volume":"22","author":"X Gao","year":"2023","unstructured":"Gao X, Zhu X, Zhai L (2023) Aoi-sensitive data collection in multi-uav-assisted wireless sensor networks. IEEE Trans Wirel Commun 22(8):5185\u20135197","journal-title":"IEEE Trans Wirel Commun"},{"key":"3218_CR40","doi-asserted-by":"crossref","unstructured":"Zhang H (2023) Analysis and prospect of existing uav path planning algorithms. In: 2023 International Conference on Power, Electrical Engineering, Electronics and Control (PEEEC). IEEE, pp. 301\u2013304","DOI":"10.1109\/PEEEC60561.2023.00064"},{"key":"3218_CR41","doi-asserted-by":"crossref","unstructured":"Liu C, Wang G, Yan Y, Bao C, Sun Y, Fan D (2010) Pint-sized military uav engine\u2019s tele-adjusting arm based on force feedback. 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics (CAR 2010), vol 2. IEEE, pp. 205\u2013209","DOI":"10.1109\/CAR.2010.5456566"},{"key":"3218_CR42","doi-asserted-by":"crossref","unstructured":"Yafei L, Anping W, Qingyang C, Yujie W (2020) An improved uav path planning method based on rrt-apf hybrid strategy. In: 2020 5th International Conference on Automation, Control and Robotics Engineering (CACRE). IEEE, pp. 81\u201386","DOI":"10.1109\/CACRE50138.2020.9229999"},{"key":"3218_CR43","doi-asserted-by":"crossref","unstructured":"Meng B (2010) Uav path planning based on bidirectional sparse a* search algorithm. In: 2010 International Conference on Intelligent Computation Technology and Automation, vol. 3, pp. 1106\u20131109. IEEE","DOI":"10.1109\/ICICTA.2010.235"},{"key":"3218_CR44","doi-asserted-by":"crossref","unstructured":"Wang X, Meng X (2019) Uav online path planning based on improved genetic algorithm. In: Chinese Control Conference (CCC). IEEE, pp. 4101\u20134106","DOI":"10.23919\/ChiCC.2019.8866205"},{"key":"3218_CR45","doi-asserted-by":"crossref","unstructured":"Wang Z, Liu L, Long T, Yu C, Kou J (2014) Enhanced sparse a* search for uav path planning using dubins path estimation. In: Proceedings of the 33rd Chinese Control Conference. IEEE, pp. 738\u2013742","DOI":"10.1109\/ChiCC.2014.6896718"},{"key":"3218_CR46","doi-asserted-by":"publisher","first-page":"7994","DOI":"10.1109\/ACCESS.2021.3049892","volume":"9","author":"Y Pan","year":"2021","unstructured":"Pan Y, Yang Y, Li W (2021) A deep learning trained by genetic algorithm to improve the efficiency of path planning for data collection with multi-uav. Ieee Access 9:7994\u20138005","journal-title":"Ieee Access"},{"key":"3218_CR47","first-page":"339","volume":"84","author":"H Samma","year":"2025","unstructured":"Samma H, El-Ferik S (2025) Uav visual path planning using large language models. Transp Res Proc 84:339\u2013345","journal-title":"Transp Res Proc"},{"key":"3218_CR48","doi-asserted-by":"crossref","unstructured":"Zhang X, Huang Y, Li J, Shao GZK, Li T, Wang X, Ning Z (2025) Ai-empowered task intent prediction and path planning for cooperative uav swarms in consumer internet of vehicles. IEEE Trans Consum Electron","DOI":"10.1109\/TCE.2025.3560642"},{"issue":"8","key":"3218_CR49","doi-asserted-by":"publisher","first-page":"2591","DOI":"10.1007\/s12555-023-0724-9","volume":"22","author":"J Ni","year":"2024","unstructured":"Ni J, Gu Y, Gu Y, Zhao Y, Shi P (2024) Uav coverage path planning with limited battery energy based on improved deep double q-network. Int J Control Autom Syst 22(8):2591\u20132601","journal-title":"Int J Control Autom Syst"},{"key":"3218_CR50","doi-asserted-by":"crossref","unstructured":"Raja G, Sivaganesh B, Ravichandran V, Saroja S, Scazzoli D, Magarini M, Dev K (2023) Ai-empowered uav trajectory optimization in 6g aerial networks. In: GLOBECOM 2023-2023 IEEE Global Communications Conference, pp. 7285\u20137290. IEEE","DOI":"10.1109\/GLOBECOM54140.2023.10436836"},{"key":"3218_CR51","doi-asserted-by":"crossref","unstructured":"Xia C, Yudi A (2018) Multi-uav path planning based on improved neural network. Chinese Control And Decision Conference (CCDC). IEEE, pp. 354\u2013359","DOI":"10.1109\/CCDC.2018.8407158"},{"issue":"2","key":"3218_CR52","doi-asserted-by":"publisher","first-page":"374","DOI":"10.23919\/JSEE.2023.000157","volume":"35","author":"J Zhang","year":"2024","unstructured":"Zhang J, Guo Y, Zheng L, Yang Q, Shi G, Wu Y (2024) Real-time uav path planning based on lstm network. J Syst Eng Electron 35(2):374\u2013385","journal-title":"J Syst Eng Electron"},{"key":"3218_CR53","doi-asserted-by":"crossref","unstructured":"Zhao Y, Zhao W, Chen L (2024) Research on path planning algorithm based on the integration of ant colony algorithm and ai decision. In: 2024 IEEE 4th International Conference on Data Science and Computer Application (ICDSCA), pp. 585\u2013589. IEEE","DOI":"10.1109\/ICDSCA63855.2024.10859913"},{"key":"3218_CR54","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121240","volume":"235","author":"A Puente-Castro","year":"2024","unstructured":"Puente-Castro A, Rivero D, Pedrosa E, Pereira A, Lau N, Fernandez-Blanco E (2024) Q-learning based system for path planning with unmanned aerial vehicles swarms in obstacle environments. Expert Syst Appl 235:121240","journal-title":"Expert Syst Appl"},{"key":"3218_CR55","doi-asserted-by":"crossref","unstructured":"Sanna G, Godio S, Guglieri G (2021) Neural network based algorithm for multi-uav coverage path planning. In: 2021 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, pp. 1210\u20131217","DOI":"10.1109\/ICUAS51884.2021.9476864"},{"issue":"8","key":"3218_CR56","doi-asserted-by":"publisher","first-page":"10998","DOI":"10.1109\/JIOT.2024.3514700","volume":"12","author":"A Xiao","year":"2025","unstructured":"Xiao A, Chen N, Wu S, Zhang P, Kuang L, Jiang C (2025) Dnfs-vne: deep neuro fuzzy system driven virtual network embedding. IEEE Internet Things J 12(8):10998\u201311010. https:\/\/doi.org\/10.1109\/JIOT.2024.3514700","journal-title":"IEEE Internet Things J"},{"issue":"3","key":"3218_CR57","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3626566","volume":"56","author":"X Xia","year":"2023","unstructured":"Xia X, Fattah SMM, Babar MA (2023) A survey on uav-enabled edge computing: resource management perspective. ACM Comput Surv 56(3):1\u201336","journal-title":"ACM Comput Surv"},{"key":"3218_CR58","doi-asserted-by":"publisher","first-page":"21699","DOI":"10.1109\/ACCESS.2023.3251698","volume":"11","author":"L Wang","year":"2023","unstructured":"Wang L, Zheng Z, Chen N, Chi Y, Liu Y, Zhu H, Zhang P, Kumar N (2023) Multi-target-aware energy orchestration modeling for grid 2.0: a network virtualization approach. IEEE Access 11:21699\u201321711","journal-title":"IEEE Access"},{"issue":"5","key":"3218_CR59","doi-asserted-by":"publisher","first-page":"2940","DOI":"10.1109\/TNSE.2022.3171600","volume":"10","author":"Z Chang","year":"2022","unstructured":"Chang Z, Deng H, You L, Min G, Garg S, Kaddoum G (2022) Trajectory design and resource allocation for multi-uav networks: deep reinforcement learning approaches. IEEE Trans Netw Sci Eng 10(5):2940\u20132951","journal-title":"IEEE Trans Netw Sci Eng"},{"key":"3218_CR60","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2021.108249","volume":"196","author":"X Chen","year":"2021","unstructured":"Chen X, Liu X, Chen Y, Jiao L, Min G (2021) Deep q-network based resource allocation for uav-assisted ultra-dense networks. Comput Netw 196:108249","journal-title":"Comput Netw"},{"issue":"10","key":"3218_CR61","doi-asserted-by":"publisher","first-page":"619","DOI":"10.3390\/drones7100619","volume":"7","author":"A Rafiq","year":"2023","unstructured":"Rafiq A, Alkanhel R, Muthanna MSA, Mokrov E, Aziz A, Muthanna A (2023) Intelligent resource allocation using an artificial ecosystem optimizer with deep learning on uav networks. Drones 7(10):619","journal-title":"Drones"},{"issue":"1","key":"3218_CR62","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1109\/TSUSC.2023.3307551","volume":"9","author":"P Zhang","year":"2023","unstructured":"Zhang P, Chen N, Kumar N, Abualigah L, Guizani M, Duan Y, Wang J, Wu S (2023) Energy allocation for vehicle-to-grid settings: a low-cost proposal combining drl and vne. IEEE Trans Sustain Comput 9(1):75\u201387","journal-title":"IEEE Trans Sustain Comput"},{"issue":"5","key":"3218_CR63","doi-asserted-by":"publisher","first-page":"3885","DOI":"10.1109\/TITS.2023.3330419","volume":"25","author":"P Zhang","year":"2023","unstructured":"Zhang P, Chen N, Xu G, Kumar N, Barnawi A, Guizani M, Duan Y, Yu K (2023) Multi-target-aware dynamic resource scheduling for cloud-fog-edge multi-tier computing network. IEEE Trans Intell Transp Syst 25(5):3885\u20133897","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"2","key":"3218_CR64","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1007\/s10515-024-00463-8","volume":"31","author":"L Tan","year":"2024","unstructured":"Tan L, Aldweesh A, Chen N, Wang J, Zhang J, Zhang Y, Kostromitin KI, Zhang P (2024) Energy efficient resource allocation based on virtual network embedding for iot data generation. Autom Softw Eng 31(2):66","journal-title":"Autom Softw Eng"},{"issue":"4","key":"3218_CR65","doi-asserted-by":"publisher","first-page":"6814","DOI":"10.1109\/TII.2024.3353848","volume":"20","author":"S Wu","year":"2024","unstructured":"Wu S, Chen N, Wen G, Xu L, Zhang P, Zhu H (2024) Virtual network embedding for task offloading in iiot: a drl-assisted federated learning scheme. IEEE Trans Industr Inf 20(4):6814\u20136824. https:\/\/doi.org\/10.1109\/TII.2024.3353848","journal-title":"IEEE Trans Industr Inf"},{"issue":"17","key":"3218_CR66","doi-asserted-by":"publisher","first-page":"15435","DOI":"10.1109\/JIOT.2022.3176400","volume":"9","author":"P McEnroe","year":"2022","unstructured":"McEnroe P, Wang S, Liyanage M (2022) A survey on the convergence of edge computing and ai for uavs: opportunities and challenges. IEEE Internet Things J 9(17):15435\u201315459","journal-title":"IEEE Internet Things J"},{"key":"3218_CR67","doi-asserted-by":"publisher","first-page":"1747","DOI":"10.1007\/s11277-012-0778-0","volume":"70","author":"E Hosseini","year":"2013","unstructured":"Hosseini E, Falahati A (2013) Improving water-filling algorithm to power control cognitive radio system based upon traffic parameters and qos. Wireless Pers Commun 70:1747\u20131759","journal-title":"Wireless Pers Commun"},{"key":"3218_CR68","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1016\/j.comcom.2019.10.014","volume":"149","author":"S Aggarwal","year":"2020","unstructured":"Aggarwal S, Kumar N (2020) Path planning techniques for unmanned aerial vehicles: a review, solutions, and challenges. Comput Commun 149:270\u2013299","journal-title":"Comput Commun"},{"key":"3218_CR69","doi-asserted-by":"publisher","first-page":"7786","DOI":"10.1109\/ACCESS.2023.3349208","volume":"12","author":"MK Banafaa","year":"2024","unstructured":"Banafaa MK, Pepeo\u011flu \u00d6, Shayea I, Alhammadi A, Shamsan ZA, Razaz MA, Alsagabi M, Al-Sowayan S (2024) A comprehensive survey on 5g-and-beyond networks with uavs: applications, emerging technologies, regulatory aspects, research trends and challenges. IEEE Access 12:7786\u20137826","journal-title":"IEEE Access"},{"key":"3218_CR70","doi-asserted-by":"crossref","unstructured":"Wang M, Shi S, Gu S, Zhang N, Gu X (2020) Intelligent resource allocation in uav-enabled mobile edge computing networks. In: 2020 IEEE 92nd Vehicular Technology Conference (VTC2020-Fall), pp. 1\u20135. IEEE","DOI":"10.1109\/VTC2020-Fall49728.2020.9348573"},{"issue":"7","key":"3218_CR71","doi-asserted-by":"publisher","first-page":"7519","DOI":"10.1109\/TVT.2022.3168277","volume":"71","author":"P Chen","year":"2022","unstructured":"Chen P, Zhou X, Zhao J, Shen F, Sun S (2022) Energy-efficient resource allocation for secure d2d communications underlaying uav-enabled networks. IEEE Trans Veh Technol 71(7):7519\u20137531","journal-title":"IEEE Trans Veh Technol"},{"key":"3218_CR72","doi-asserted-by":"crossref","unstructured":"Feng W, Tang J, Zhao N, Zhang X, Wang X, Wong K-K (2021) A deep learning-based approach to resource allocation in uav-aided wireless powered mec networks. In: ICC 2021-IEEE International Conference on Communications. IEEE, pp. 1\u20136","DOI":"10.1109\/ICC42927.2021.9500582"},{"key":"3218_CR73","doi-asserted-by":"crossref","unstructured":"Cai Y, Zhang E, Qi Y, Lu L (2022) A review of research on the application of deep reinforcement learning in unmanned aerial vehicle resource allocation and trajectory planning. In: 2022 4th International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI). IEEE, pp. 238\u2013241","DOI":"10.1109\/MLBDBI58171.2022.00053"},{"issue":"2","key":"3218_CR74","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1109\/TNSE.2021.3117565","volume":"9","author":"M Chen","year":"2021","unstructured":"Chen M, Liu A, Liu W, Ota K, Dong M, Xiong NN (2021) Rdrl: a recurrent deep reinforcement learning scheme for dynamic spectrum access in reconfigurable wireless networks. IEEE Trans Netw Sci Eng 9(2):364\u2013376","journal-title":"IEEE Trans Netw Sci Eng"},{"issue":"7","key":"3218_CR75","doi-asserted-by":"publisher","first-page":"7952","DOI":"10.1109\/TVT.2022.3166535","volume":"71","author":"F Li","year":"2022","unstructured":"Li F, Shen B, Guo J, Lam K-Y, Wei G, Wang L (2022) Dynamic spectrum access for internet-of-things based on federated deep reinforcement learning. IEEE Trans Veh Technol 71(7):7952\u20137956","journal-title":"IEEE Trans Veh Technol"},{"issue":"14","key":"3218_CR76","doi-asserted-by":"publisher","first-page":"11208","DOI":"10.1109\/JIOT.2021.3052691","volume":"8","author":"H Song","year":"2021","unstructured":"Song H, Liu L, Ashdown J, Yi Y (2021) A deep reinforcement learning framework for spectrum management in dynamic spectrum access. IEEE Internet Things J 8(14):11208\u201311218","journal-title":"IEEE Internet Things J"},{"issue":"12","key":"3218_CR77","doi-asserted-by":"publisher","first-page":"10934","DOI":"10.1109\/TWC.2022.3188302","volume":"21","author":"S Zhang","year":"2022","unstructured":"Zhang S, Gu H, Chi K, Huang L, Yu K, Mumtaz S (2022) Drl-based partial offloading for maximizing sum computation rate of wireless powered mobile edge computing network. IEEE Trans Wireless Commun 21(12):10934\u201310948","journal-title":"IEEE Trans Wireless Commun"},{"issue":"4","key":"3218_CR78","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1016\/j.dcan.2020.04.008","volume":"6","author":"J Chen","year":"2020","unstructured":"Chen J, Chen S, Luo S, Wang Q, Cao B, Li X (2020) An intelligent task offloading algorithm (itoa) for uav edge computing network. Digital Commun Netw 6(4):433\u2013443","journal-title":"Digital Commun Netw"},{"key":"3218_CR79","doi-asserted-by":"crossref","unstructured":"Yang J, Zhu K, Zhu X, Wang J (2021) Learning-based aerial charging scheduling for uav-based data collection. In: Wireless Algorithms, Systems, and Applications: 16th International Conference, WASA 2021, Nanjing, China, June 25\u201327, 2021, Proceedings, Part II 16, pp. 600\u2013611. Springer","DOI":"10.1007\/978-3-030-86130-8_47"},{"key":"3218_CR80","doi-asserted-by":"crossref","unstructured":"Marini R, Park S, Simeone O, Buratti C (2023) Continual meta-reinforcement learning for uav-aided vehicular wireless networks. In: ICC 2023-IEEE International Conference on Communications. IEEE, pp 5664\u20135669","DOI":"10.1109\/ICC45041.2023.10279524"},{"issue":"3","key":"3218_CR81","doi-asserted-by":"publisher","first-page":"1495","DOI":"10.1109\/TWC.2022.3204794","volume":"22","author":"X Zhang","year":"2022","unstructured":"Zhang X, Zhao H, Wei J, Yan C, Xiong J, Liu X (2022) Cooperative trajectory design of multiple uav base stations with heterogeneous graph neural networks. IEEE Trans Wireless Commun 22(3):1495\u20131509","journal-title":"IEEE Trans Wireless Commun"},{"issue":"17","key":"3218_CR82","doi-asserted-by":"publisher","first-page":"4377","DOI":"10.3390\/rs14174377","volume":"14","author":"X Wang","year":"2022","unstructured":"Wang X, Fu L, Cheng N, Sun R, Luan T, Quan W, Aldubaikhy K (2022) Joint flying relay location and routing optimization for 6g uav-iot networks: a graph neural network-based approach. Remote Sens 14(17):4377","journal-title":"Remote Sens"},{"issue":"4","key":"3218_CR83","doi-asserted-by":"publisher","first-page":"3038","DOI":"10.1109\/COMST.2023.3323344","volume":"25","author":"Y Bai","year":"2023","unstructured":"Bai Y, Zhao H, Zhang X, Chang Z, J\u00e4ntti R, Yang K (2023) Toward autonomous multi-uav wireless network: a survey of reinforcement learning-based approaches. IEEE Commun Surv Tutor 25(4):3038\u20133067","journal-title":"IEEE Commun Surv Tutor"},{"key":"3218_CR84","doi-asserted-by":"crossref","unstructured":"Zhang W, Yang D, Wu W, Peng H, Zhang H, Shen XS (2021) Spectrum and computing resource management for federated learning in distributed industrial iot. In: 2021 IEEE International Conference on Communications Workshops (ICC Workshops), pp 1\u20136. IEEE","DOI":"10.1109\/ICCWorkshops50388.2021.9473515"},{"key":"3218_CR85","doi-asserted-by":"crossref","unstructured":"Tang X, Chen Q, Weng W, Liao B, Wang J, Cao X, Li X (2025) Dnn task assignment in uav networks: a generative ai enhanced multi-agent reinforcement learning approach. IEEE Internet Things J","DOI":"10.1109\/JIOT.2025.3541715"},{"issue":"4","key":"3218_CR86","doi-asserted-by":"publisher","first-page":"2933","DOI":"10.1109\/JIOT.2021.3094651","volume":"9","author":"S Yin","year":"2021","unstructured":"Yin S, Yu FR (2021) Resource allocation and trajectory design in uav-aided cellular networks based on multiagent reinforcement learning. IEEE Internet Things J 9(4):2933\u20132943","journal-title":"IEEE Internet Things J"},{"issue":"19","key":"3218_CR87","doi-asserted-by":"publisher","first-page":"19477","DOI":"10.1109\/JIOT.2022.3168296","volume":"9","author":"X Tan","year":"2022","unstructured":"Tan X, Zhou L, Wang H, Sun Y, Zhao H, Seet B-C, Wei J, Leung VC (2022) Cooperative multi-agent reinforcement-learning-based distributed dynamic spectrum access in cognitive radio networks. IEEE Internet Things J 9(19):19477\u201319488","journal-title":"IEEE Internet Things J"},{"key":"3218_CR88","doi-asserted-by":"crossref","unstructured":"Ma M, Wang C, Li Z, Liu F (2024) A proactive resource allocation algorithm for uav-assisted v2x communication based on dynamic multi-objective optimization. IEEE Commun Lett","DOI":"10.1109\/LCOMM.2024.3488123"},{"issue":"5","key":"3218_CR89","doi-asserted-by":"publisher","first-page":"4691","DOI":"10.1109\/TWC.2023.3321648","volume":"23","author":"H Pan","year":"2023","unstructured":"Pan H, Liu Y, Sun G, Wang P, Yuen C (2023) Resource scheduling for uavs-aided d2d networks: a multi-objective optimization approach. IEEE Trans Wireless Commun 23(5):4691\u20134708","journal-title":"IEEE Trans Wireless Commun"},{"key":"3218_CR90","doi-asserted-by":"crossref","unstructured":"Wu G, Liu Z, Fan M, Wu K (2024) Joint task offloading and resource allocation in multi-uav multi-server systems: an attention-based deep reinforcement learning approach. IEEE Trans Veh Technol","DOI":"10.1109\/TVT.2024.3377647"},{"issue":"5","key":"3218_CR91","doi-asserted-by":"publisher","first-page":"358","DOI":"10.3390\/drones9050358","volume":"9","author":"T Wang","year":"2025","unstructured":"Wang T, Na X, Nie Y, Liu J, Wang W, Meng Z (2025) Parallel task offloading and trajectory optimization for uav-assisted mobile edge computing via hierarchical reinforcement learning. Drones 9(5):358","journal-title":"Drones"},{"key":"3218_CR92","doi-asserted-by":"publisher","DOI":"10.1016\/j.ast.2024.109131","volume":"149","author":"C Mu","year":"2024","unstructured":"Mu C, Liu S, Lu M, Liu Z, Cui L, Wang K (2024) Autonomous spacecraft collision avoidance with a variable number of space debris based on safe reinforcement learning. Aerosp Sci Technol 149:109131","journal-title":"Aerosp Sci Technol"},{"issue":"4","key":"3218_CR93","doi-asserted-by":"publisher","first-page":"991","DOI":"10.1109\/TCCN.2023.3262242","volume":"9","author":"AM Seid","year":"2023","unstructured":"Seid AM, Erbad A, Abishu HN, Albaseer A, Abdallah M, Guizani M (2023) Blockchain-empowered resource allocation in multi-uav-enabled 5g-ran: A multi-agent deep reinforcement learning approach. IEEE Trans Cogn Commun Netw 9(4):991\u20131011","journal-title":"IEEE Trans Cogn Commun Netw"},{"issue":"12","key":"3218_CR94","doi-asserted-by":"publisher","first-page":"10187","DOI":"10.1109\/JIOT.2021.3122014","volume":"9","author":"Z Li","year":"2021","unstructured":"Li Z, Liao X, Shi J, Li L, Xiao P (2021) Md-gan-based uav trajectory and power optimization for cognitive covert communications. IEEE Internet Things J 9(12):10187\u201310199","journal-title":"IEEE Internet Things J"},{"key":"3218_CR95","doi-asserted-by":"crossref","unstructured":"Zhao H, Lu G, Liu Y, Chang Z, Wang L, H\u00e4m\u00e4l\u00e4inen T (2024) Safe dqn-based aoi-minimal task offloading for uav-aided edge computing system. IEEE Internet Things J","DOI":"10.1109\/JIOT.2024.3422670"},{"issue":"4","key":"3218_CR96","doi-asserted-by":"publisher","first-page":"1101","DOI":"10.1109\/JSAC.2020.3018804","volume":"39","author":"S Khairy","year":"2020","unstructured":"Khairy S, Balaprakash P, Cai LX, Cheng Y (2020) Constrained deep reinforcement learning for energy sustainable multi-uav based random access iot networks with noma. IEEE J Sel Areas Commun 39(4):1101\u20131115","journal-title":"IEEE J Sel Areas Commun"},{"key":"3218_CR97","unstructured":"Muchiri G, Kimathi S (2022) A review of applications and potential applications of uav. Proc Sustain Res Innov Conf:280\u2013283"},{"key":"3218_CR98","doi-asserted-by":"crossref","unstructured":"Cheng Y, Song Y (2020) Autonomous decision-making generation of uav based on soft actor-critic algorithm. In: 2020 39th Chinese Control Conference (ccc). IEEE, pp. 7350\u20137355","DOI":"10.23919\/CCC50068.2020.9188886"},{"key":"3218_CR99","doi-asserted-by":"crossref","unstructured":"Zhou Y, Chen S, Wang Y, Huan W (2020) Review of research on lightweight convolutional neural networks. In: 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC). IEEE, pp. 1713\u20131720","DOI":"10.1109\/ITOEC49072.2020.9141847"},{"issue":"11","key":"3218_CR100","doi-asserted-by":"publisher","first-page":"1778","DOI":"10.1109\/JPROC.2021.3119950","volume":"109","author":"D Xu","year":"2021","unstructured":"Xu D, Li T, Li Y, Su X, Tarkoma S, Jiang T, Crowcroft J, Hui P (2021) Edge intelligence: empowering intelligence to the edge of network. Proc IEEE 109(11):1778\u20131837","journal-title":"Proc IEEE"},{"key":"3218_CR101","doi-asserted-by":"crossref","unstructured":"Varghese B, Wang N, Barbhuiya S, Kilpatrick P, Nikolopoulos DS (2016) Challenges and opportunities in edge computing. In: 2016 IEEE International Conference on Smart Cloud (SmartCloud). IEEE, pp. 20\u201326","DOI":"10.1109\/SmartCloud.2016.18"},{"key":"3218_CR102","unstructured":"Chen Z, Zhu B, Zhou C (2023) Container cluster placement in edge computing based on reinforcement learning incorporating graph convolutional networks scheme. Digit Commun Netw"},{"issue":"3","key":"3218_CR103","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1109\/JAS.2021.1004261","volume":"9","author":"J Zhang","year":"2021","unstructured":"Zhang J, Pan L, Han Q-L, Chen C, Wen S, Xiang Y (2021) Deep learning based attack detection for cyber-physical system cybersecurity: a survey. IEEE\/CAA J Automat Sinica 9(3):377\u2013391","journal-title":"IEEE\/CAA J Automat Sinica"},{"key":"3218_CR104","doi-asserted-by":"crossref","unstructured":"Hua M, Huang Y, Sun Y, Wang Y, Yang L (2018) Energy optimization for cellular-connected uav mobile edge computing systems. In: 2018 IEEE International Conference on Communication Systems (ICCS), pp. 1\u20136. IEEE","DOI":"10.1109\/ICCS.2018.8689226"},{"key":"3218_CR105","doi-asserted-by":"crossref","unstructured":"Bi J, Cheng X, Yuan H, Niu S, Zhai J (2024) Resource allocation and trajectory optimization in unmanned aerial vehicle-assisted mobile edge computing. In: 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, pp. 858\u2013863","DOI":"10.1109\/SMC54092.2024.10831300"},{"key":"3218_CR106","doi-asserted-by":"publisher","first-page":"180784","DOI":"10.1109\/ACCESS.2020.3028553","volume":"8","author":"H Wang","year":"2020","unstructured":"Wang H, Ke H, Sun W (2020) Unmanned-aerial-vehicle-assisted computation offloading for mobile edge computing based on deep reinforcement learning. IEEE Access 8:180784\u2013180798","journal-title":"IEEE Access"},{"issue":"19","key":"3218_CR107","doi-asserted-by":"publisher","first-page":"18208","DOI":"10.1109\/JIOT.2022.3155608","volume":"9","author":"X Duan","year":"2022","unstructured":"Duan X, Zhou Y, Tian D, Zhou J, Sheng Z, Shen X (2022) Weighted energy-efficiency maximization for a uav-assisted multiplatoon mobile-edge computing system. IEEE Internet Things J 9(19):18208\u201318220","journal-title":"IEEE Internet Things J"},{"issue":"6","key":"3218_CR108","doi-asserted-by":"publisher","first-page":"824","DOI":"10.1631\/FITEE.2300393","volume":"25","author":"Y Li","year":"2024","unstructured":"Li Y, Wei Z, Su J, Zhao B (2024) A multi-agent collaboration scheme for energy-efficient task scheduling in a 3d uav-mec space. Front Inform Technol Electron Eng 25(6):824\u2013838","journal-title":"Front Inform Technol Electron Eng"},{"issue":"6","key":"3218_CR109","doi-asserted-by":"publisher","first-page":"172","DOI":"10.1109\/MWC.2019.1900025","volume":"26","author":"K Lu","year":"2019","unstructured":"Lu K, Xie J, Wan Y, Fu S (2019) Toward uav-based airborne computing. IEEE Wirel Commun 26(6):172\u2013179","journal-title":"IEEE Wirel Commun"},{"issue":"4","key":"3218_CR110","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1109\/MCE.2022.3181759","volume":"13","author":"C-H Wang","year":"2022","unstructured":"Wang C-H, Huang K-Y, Yao Y, Chen J-C, Shuai H-H, Cheng W-H (2022) Lightweight deep learning: an overview. IEEE Consum Electron Mag 13(4):51\u201364","journal-title":"IEEE Consum Electron Mag"},{"issue":"7","key":"3218_CR111","doi-asserted-by":"publisher","first-page":"166","DOI":"10.3390\/drones6070166","volume":"6","author":"G Zhan","year":"2022","unstructured":"Zhan G, Zhang X, Li Z, Xu L, Zhou D, Yang Z (2022) Multiple-uav reinforcement learning algorithm based on improved ppo in ray framework. Drones 6(7):166","journal-title":"Drones"},{"issue":"3","key":"3218_CR112","first-page":"337","volume":"33","author":"C Rong","year":"2021","unstructured":"Rong C, Fei Z, Sha L, Qianbin C (2021) 6g mobile communication: vision, key technologies and system architecture. J Chong Univ Posts Telecommun (Natl Sci Ed) 33(3):337\u2013347","journal-title":"J Chong Univ Posts Telecommun (Natl Sci Ed)"},{"key":"3218_CR113","doi-asserted-by":"crossref","unstructured":"Lu M, Fan X, Chen H, Lu P (2024) Fapp: Fast and adaptive perception and planning for uavs in dynamic cluttered environments. IEEE Trans Robot","DOI":"10.1109\/TRO.2024.3522187"},{"key":"3218_CR114","doi-asserted-by":"crossref","unstructured":"Lyu H (2018) Detect and avoid system based on multi sensor fusion for uav. In: 2018 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, pp. 1107\u20131109","DOI":"10.1109\/ICTC.2018.8539587"},{"key":"3218_CR115","doi-asserted-by":"publisher","first-page":"105139","DOI":"10.1109\/ACCESS.2020.3000064","volume":"8","author":"JN Yasin","year":"2020","unstructured":"Yasin JN, Mohamed SA, Haghbayan M-H, Heikkonen J, Tenhunen H, Plosila J (2020) Unmanned aerial vehicles (uavs): collision avoidance systems and approaches. IEEE Access 8:105139\u2013105155","journal-title":"IEEE Access"},{"issue":"4","key":"3218_CR116","first-page":"142","volume":"44","author":"C Sun","year":"2019","unstructured":"Sun C, Zhao H, Wang Y, Zhou H, Han J (2019) Ucav autonomic maneuver decision-making method based on reinforcement learning. Fire Control Command Control 44(4):142\u2013149","journal-title":"Fire Control Command Control"},{"issue":"1","key":"3218_CR117","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/TCCN.2020.3027695","volume":"7","author":"L Wang","year":"2020","unstructured":"Wang L, Wang K, Pan C, Xu W, Aslam N, Hanzo L (2020) Multi-agent deep reinforcement learning-based trajectory planning for multi-uav assisted mobile edge computing. IEEE Trans Cogn Commun Netw 7(1):73\u201384","journal-title":"IEEE Trans Cogn Commun Netw"},{"issue":"2","key":"3218_CR118","doi-asserted-by":"publisher","first-page":"1782","DOI":"10.1109\/TVT.2021.3051378","volume":"70","author":"D Callegaro","year":"2021","unstructured":"Callegaro D, Levorato M (2021) Optimal edge computing for infrastructure-assisted uav systems. IEEE Trans Veh Technol 70(2):1782\u20131792","journal-title":"IEEE Trans Veh Technol"},{"issue":"4","key":"3218_CR119","first-page":"560","volume":"21","author":"Y Bai","year":"2019","unstructured":"Bai Y, Chen X, Yuan J (2019) Statistical analysis technology of uas cloud data exchange platform based on big data [j]. J Geo-inform Sci 21(4):560\u2013569","journal-title":"J Geo-inform Sci"},{"key":"3218_CR120","volume":"55","author":"R Ch","year":"2020","unstructured":"Ch R, Srivastava G, Gadekallu TR, Maddikunta PKR, Bhattacharya S (2020) Security and privacy of uav data using blockchain technology. J Inform Secur Appl 55:102670","journal-title":"J Inform Secur Appl"},{"issue":"05","key":"3218_CR121","first-page":"150","volume":"42","author":"D He","year":"2019","unstructured":"He D, Du X, Qiao Y, Zhu Y, Fan Q, Luo W (2019) A survey on cyber security of unmanned aerial vehicles. Chin J Comput 42(05):150\u2013168","journal-title":"Chin J Comput"},{"key":"3218_CR122","doi-asserted-by":"crossref","unstructured":"Zhang Y, Li C, Chen N, Zhang P (2022) Intelligent requests orchestration for microservice management based on blockchain in software defined networking: A security guarantee. In: 2022 IEEE International Conference on Communications Workshops (ICC Workshops), pp. 254\u2013259. IEEE","DOI":"10.1109\/ICCWorkshops53468.2022.9814536"},{"key":"3218_CR123","doi-asserted-by":"publisher","first-page":"29393","DOI":"10.1109\/ACCESS.2022.3158666","volume":"10","author":"Y Duan","year":"2022","unstructured":"Duan Y, Chen N, Chang L, Ni Y, Kumar SS, Zhang P (2022) Capso: Chaos adaptive particle swarm optimization algorithm. Ieee Access 10:29393\u201329405","journal-title":"Ieee Access"},{"key":"3218_CR124","doi-asserted-by":"crossref","unstructured":"Volovoda T (2024) Swarm intelligence for uav. In: 2024 IEEE 7th International Conference on Actual Problems of Unmanned Aerial Vehicles Development (APUAVD). IEEE, pp. 313\u2013316","DOI":"10.1109\/APUAVD64488.2024.10765878"},{"key":"3218_CR125","doi-asserted-by":"crossref","unstructured":"Yang F, Wang P, Zhang Y, Zheng L, Lu J (2017) Survey of swarm intelligence optimization algorithms. In: 2017 IEEE International Conference on Unmanned Systems (ICUS). IEEE, pp. 544\u2013549","DOI":"10.1109\/ICUS.2017.8278405"},{"key":"3218_CR126","doi-asserted-by":"crossref","unstructured":"Li X, Zhou H (2023) Uav formation centralized control method under cooperative flight missions. In: 2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI). IEEE, pp. 366\u2013369","DOI":"10.1109\/RICAI60863.2023.10489720"},{"issue":"1","key":"3218_CR127","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1109\/JSAC.2020.3036962","volume":"39","author":"H Peng","year":"2020","unstructured":"Peng H, Shen X (2020) Multi-agent reinforcement learning based resource management in mec-and uav-assisted vehicular networks. IEEE J Sel Areas Commun 39(1):131\u2013141","journal-title":"IEEE J Sel Areas Commun"},{"issue":"6","key":"3218_CR128","doi-asserted-by":"publisher","first-page":"1262","DOI":"10.1109\/JSAC.2019.2904353","volume":"37","author":"CH Liu","year":"2019","unstructured":"Liu CH, Chen Z, Zhan Y (2019) Energy-efficient distributed mobile crowd sensing: a deep learning approach. IEEE J Sel Areas Commun 37(6):1262\u20131276","journal-title":"IEEE J Sel Areas Commun"},{"key":"3218_CR129","doi-asserted-by":"crossref","unstructured":"Emami Y, Wei B, Li K, Ni W, Tovar E (2021) Deep q-networks for aerial data collection in multi-uav-assisted wireless sensor networks. In: 2021 International Wireless Communications and Mobile Computing (IWCMC). IEEE, pp. 669\u2013674","DOI":"10.1109\/IWCMC51323.2021.9498726"},{"issue":"2","key":"3218_CR130","doi-asserted-by":"publisher","first-page":"1055","DOI":"10.1109\/TNSE.2020.3014385","volume":"8","author":"Y Wang","year":"2020","unstructured":"Wang Y, Su Z, Zhang N, Benslimane A (2020) Learning in the air: secure federated learning for uav-assisted crowdsensing. IEEE Trans Netw Sci Eng 8(2):1055\u20131069","journal-title":"IEEE Trans Netw Sci Eng"},{"issue":"2","key":"3218_CR131","doi-asserted-by":"publisher","first-page":"3098","DOI":"10.1109\/LRA.2020.2974648","volume":"5","author":"D Wang","year":"2020","unstructured":"Wang D, Fan T, Han T, Pan J (2020) A two-stage reinforcement learning approach for multi-uav collision avoidance under imperfect sensing. IEEE Robot Autom Lett 5(2):3098\u20133105","journal-title":"IEEE Robot Autom Lett"},{"issue":"10","key":"3218_CR132","doi-asserted-by":"publisher","first-page":"10986","DOI":"10.1109\/TVT.2021.3110801","volume":"70","author":"Y Emami","year":"2021","unstructured":"Emami Y, Wei B, Li K, Ni W, Tovar E (2021) Joint communication scheduling and velocity control in multi-uav-assisted sensor networks: a deep reinforcement learning approach. IEEE Trans Veh Technol 70(10):10986\u201310998","journal-title":"IEEE Trans Veh Technol"},{"issue":"3","key":"3218_CR133","doi-asserted-by":"publisher","first-page":"955","DOI":"10.1109\/TCCN.2021.3063170","volume":"7","author":"F Venturini","year":"2021","unstructured":"Venturini F, Mason F, Pase F, Chiariotti F, Testolin A, Zanella A, Zorzi M (2021) Distributed reinforcement learning for flexible and efficient uav swarm control. IEEE Trans Cogn Commun Netw 7(3):955\u2013969","journal-title":"IEEE Trans Cogn Commun Netw"},{"issue":"1","key":"3218_CR134","doi-asserted-by":"publisher","first-page":"931","DOI":"10.1109\/TVT.2021.3129504","volume":"71","author":"Z Xia","year":"2021","unstructured":"Xia Z, Du J, Wang J, Jiang C, Ren Y, Li G, Han Z (2021) Multi-agent reinforcement learning aided intelligent uav swarm for target tracking. IEEE Trans Veh Technol 71(1):931\u2013945","journal-title":"IEEE Trans Veh Technol"},{"issue":"10","key":"3218_CR135","doi-asserted-by":"publisher","first-page":"7086","DOI":"10.1109\/TII.2022.3143175","volume":"18","author":"WJ Yun","year":"2022","unstructured":"Yun WJ, Park S, Kim J, Shin M, Jung S, Mohaisen DA, Kim J-H (2022) Cooperative multiagent deep reinforcement learning for reliable surveillance via autonomous multi-uav control. IEEE Trans Ind Inf 18(10):7086\u20137096","journal-title":"IEEE Trans Ind Inf"},{"issue":"9","key":"3218_CR136","doi-asserted-by":"publisher","first-page":"6949","DOI":"10.1109\/TWC.2022.3153316","volume":"21","author":"N Zhao","year":"2022","unstructured":"Zhao N, Ye Z, Pei Y, Liang Y-C, Niyato D (2022) Multi-agent deep reinforcement learning for task offloading in uav-assisted mobile edge computing. IEEE Trans Wirel Commun 21(9):6949\u20136960","journal-title":"IEEE Trans Wirel Commun"},{"issue":"10","key":"3218_CR137","doi-asserted-by":"publisher","first-page":"7900","DOI":"10.1109\/TNNLS.2022.3146976","volume":"34","author":"R Zhang","year":"2022","unstructured":"Zhang R, Zong Q, Zhang X, Dou L, Tian B (2022) Game of drones: Multi-uav pursuit-evasion game with online motion planning by deep reinforcement learning. IEEE Trans Neural Netw Learn Syst 34(10):7900\u20137909","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"5","key":"3218_CR138","doi-asserted-by":"publisher","first-page":"3786","DOI":"10.1109\/JIOT.2020.3024666","volume":"8","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Mou Z, Gao F, Xing L, Jiang J, Han Z (2020) Hierarchical deep reinforcement learning for backscattering data collection with multiple uavs. IEEE Internet Things J 8(5):3786\u20133800","journal-title":"IEEE Internet Things J"},{"issue":"15","key":"3218_CR139","doi-asserted-by":"publisher","first-page":"13823","DOI":"10.1109\/JIOT.2022.3142269","volume":"9","author":"Y Liu","year":"2022","unstructured":"Liu Y, Yan J, Zhao X (2022) Deep-reinforcement-learning-based optimal transmission policies for opportunistic uav-aided wireless sensor network. IEEE Internet Things J 9(15):13823\u201313836","journal-title":"IEEE Internet Things J"},{"issue":"17","key":"3218_CR140","doi-asserted-by":"publisher","first-page":"16663","DOI":"10.1109\/JIOT.2022.3153585","volume":"9","author":"X Wang","year":"2022","unstructured":"Wang X, Gursoy MC, Erpek T, Sagduyu YE (2022) Learning-based uav path planning for data collection with integrated collision avoidance. IEEE Internet Things J 9(17):16663\u201316676","journal-title":"IEEE Internet Things J"},{"issue":"3","key":"3218_CR141","doi-asserted-by":"publisher","first-page":"165","DOI":"10.3390\/drones7030165","volume":"7","author":"N Chen","year":"2023","unstructured":"Chen N, Shen S, Duan Y, Huang S, Zhang W, Tan L (2023) Non-euclidean graph-convolution virtual network embedding for space-air-ground integrated networks. Drones 7(3):165","journal-title":"Drones"},{"key":"3218_CR142","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109931","volume":"257","author":"N Chen","year":"2022","unstructured":"Chen N, Zhang P, Kumar N, Hsu C-H, Abualigah L, Zhu H (2022) Spectral graph theory-based virtual network embedding for vehicular fog computing: a deep reinforcement learning architecture. Knowl-Based Syst 257:109931","journal-title":"Knowl-Based Syst"},{"key":"3218_CR143","doi-asserted-by":"publisher","unstructured":"Chen N, Xiao A, Wu S, Li C, Ji Z, Kuang L (2026) Cell clustering beam hopping with interference avoidance: A coopmasac-psct framework. IEEE Internet Things J:1\u20131. https:\/\/doi.org\/10.1109\/JIOT.2026.3670442","DOI":"10.1109\/JIOT.2026.3670442"},{"key":"3218_CR144","doi-asserted-by":"crossref","unstructured":"Scott-Hayward S (2023) Secure, intelligent, programmable space-air-ground integrated networks. In: Proceedings of the 2023 Workshop on Recent Advances in Resilient and Trustworthy ML Systems in Autonomous Networks, pp. 1\u20131","DOI":"10.1145\/3605772.3625393"},{"key":"3218_CR145","doi-asserted-by":"publisher","first-page":"6405","DOI":"10.1109\/TCCN.2026.3665891","volume":"12","author":"N Chen","year":"2026","unstructured":"Chen N, Xiao A, Wu S, Ji Z, Jia H, Kuang L (2026) Multi-stage survivable network slicing with load balancing for leo mega-constellation. IEEE Trans Cogn Commun Netw 12:6405\u20136420. https:\/\/doi.org\/10.1109\/TCCN.2026.3665891","journal-title":"IEEE Trans Cogn Commun Netw"},{"key":"3218_CR146","doi-asserted-by":"crossref","unstructured":"Pagliari E, Davoli L, Cicioni G, Palazzi V, Ferrari G (2024) On uav terrestrial connectivity enhancement through smart selective antennas. In: Journal of Physics: Conference Series, vol. 2716, pp. 012057. IOP Publishing","DOI":"10.1088\/1742-6596\/2716\/1\/012057"},{"key":"3218_CR147","doi-asserted-by":"crossref","unstructured":"Kawamoto Y, Okawara Y, Verma S, Kato N, Kaneko K, Sata A, Ochiai M (2024) Interference suppression in haps-based space-air-ground integrated networks using a codebook-based approach. IEEE Trans Veh Technol","DOI":"10.1109\/TVT.2024.3446999"},{"issue":"23","key":"3218_CR148","doi-asserted-by":"publisher","first-page":"20511","DOI":"10.1109\/JIOT.2023.3288121","volume":"10","author":"N Yang","year":"2023","unstructured":"Yang N, Guo D, Jiao Y, Ding G, Qu T (2023) Lightweight blockchain-based secure spectrum sharing in space-air-ground-integrated iot network. IEEE Internet Things J 10(23):20511\u201320527","journal-title":"IEEE Internet Things J"},{"issue":"5","key":"3218_CR149","doi-asserted-by":"publisher","first-page":"3364","DOI":"10.1109\/TCOMM.2022.3159703","volume":"70","author":"W Lu","year":"2022","unstructured":"Lu W, Ding Y, Gao Y, Chen Y, Zhao N, Ding Z, Nallanathan A (2022) Secure noma-based uav-mec network towards a flying eavesdropper. IEEE Trans Commun 70(5):3364\u20133376","journal-title":"IEEE Trans Commun"},{"issue":"2","key":"3218_CR150","doi-asserted-by":"publisher","first-page":"166","DOI":"10.23919\/JCN.2021.000045","volume":"24","author":"A Misra","year":"2022","unstructured":"Misra A, Sarma MP, Sarma KK, Mastorakis N (2022) Temporal deep learning assisted uav communication channel model for application in eh-mimo-noma set-up. J Commun Netw 24(2):166\u2013183","journal-title":"J Commun Netw"},{"key":"3218_CR151","doi-asserted-by":"crossref","unstructured":"Boroujeni SPH, Razi A, Khoshdel S, Afghah F, Coen JL, O\u2019Neill L, Fule P, Watts A, Kokolakis NMT, Vamvoudakis KG (2024) A comprehensive survey of research towards ai-enabled unmanned aerial systems in pre-, active-, and post-wildfire management. Inform Fus:102369","DOI":"10.1016\/j.inffus.2024.102369"},{"issue":"1","key":"3218_CR152","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1109\/MPRV.2017.11","volume":"16","author":"M Erdelj","year":"2017","unstructured":"Erdelj M, Natalizio E, Chowdhury KR, Akyildiz IF (2017) Help from the sky: leveraging uavs for disaster management. IEEE Pervasive Comput 16(1):24\u201332","journal-title":"IEEE Pervasive Comput"},{"issue":"11","key":"3218_CR153","doi-asserted-by":"publisher","first-page":"840","DOI":"10.1071\/WF19008","volume":"28","author":"J Arkin","year":"2019","unstructured":"Arkin J, Coops NC, Hermosilla T, Daniels LD, Plowright A (2019) Integrated fire severity-land cover mapping using very-high-spatial-resolution aerial imagery and point clouds. Int J Wildland Fire 28(11):840\u2013860","journal-title":"Int J Wildland Fire"},{"key":"3218_CR154","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2022.113203","volume":"280","author":"V Martins","year":"2022","unstructured":"Martins V, Roy D, Huang H, Boschetti L, Zhang H, Yan L (2022) Deep learning high resolution burned area mapping by transfer learning from landsat-8 to planetscope. Remote Sens Environ 280:113203","journal-title":"Remote Sens Environ"},{"issue":"4","key":"3218_CR155","doi-asserted-by":"publisher","first-page":"2633","DOI":"10.1109\/COMST.2022.3199901","volume":"24","author":"MM Azari","year":"2022","unstructured":"Azari MM, Solanki S, Chatzinotas S, Kodheli O, Sallouha H, Colpaert A, Montoya JFM, Pollin S, Haqiqatnejad A, Mostaani A et al (2022) Evolution of non-terrestrial networks from 5g to 6g: a survey. IEEE commun Surv Tutor 24(4):2633\u20132672","journal-title":"IEEE commun Surv Tutor"},{"issue":"12","key":"3218_CR156","doi-asserted-by":"publisher","first-page":"4311","DOI":"10.3390\/s18124311","volume":"18","author":"A Colpaert","year":"2018","unstructured":"Colpaert A, Vinogradov E, Pollin S (2018) Aerial coverage analysis of cellular systems at lte and mmwave frequencies using 3d city models. Sensors 18(12):4311","journal-title":"Sensors"},{"issue":"4","key":"3218_CR157","doi-asserted-by":"publisher","first-page":"2275","DOI":"10.1109\/TWC.2021.3110785","volume":"21","author":"SS Kalamkar","year":"2021","unstructured":"Kalamkar SS, Baccelli F, Abinader FM, Fani ASM, Garcia LGU (2021) Beam management in 5g: a stochastic geometry analysis. IEEE Trans Wirel Commun 21(4):2275\u20132290","journal-title":"IEEE Trans Wirel Commun"},{"key":"3218_CR158","doi-asserted-by":"crossref","unstructured":"Colpaert A, Vinogradov E, Pollin S (2020) 3d beamforming and handover analysis for uav networks. In: 2020 IEEE Globecom Workshops GC Wkshps. IEEE, pp. 1\u20136","DOI":"10.1109\/GCWkshps50303.2020.9367570"},{"issue":"1","key":"3218_CR159","doi-asserted-by":"publisher","first-page":"38","DOI":"10.3390\/info15010038","volume":"15","author":"X Wang","year":"2024","unstructured":"Wang X, Guo Y, Gao Y (2024) Unmanned autonomous intelligent system in 6g non-terrestrial network. Information 15(1):38","journal-title":"Information"},{"key":"3218_CR160","doi-asserted-by":"crossref","unstructured":"Traspadini A, Giordani M, Zorzi M (2022) Uav\/hap-assisted vehicular edge computing in 6g: Where and what to offload? In: 2022 Joint European Conference on Networks and Communications & 6G Summit (EuCNC\/6G Summit), pp. 178\u2013183. IEEE","DOI":"10.1109\/EuCNC\/6GSummit54941.2022.9815734"},{"key":"3218_CR161","doi-asserted-by":"crossref","unstructured":"Matthew UO, Kazaure JS, Onyebuchi A, Daniel OO, Muhammed IH, Okafor NU (2021) Artificial intelligence autonomous unmanned aerial vehicle (uav) system for remote sensing in security surveillance. In: 2020 IEEE 2nd International Conference on Cyberspac (CYBER NIGERIA). IEEE, pp. 1\u201310","DOI":"10.1109\/CYBERNIGERIA51635.2021.9428862"},{"key":"3218_CR162","doi-asserted-by":"crossref","unstructured":"Testi E, Favarelli E, Giorgetti A (2020) Reinforcement learning for connected autonomous vehicle localization via uavs. In: 2020 IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor). IEEE, pp. 13\u201317","DOI":"10.1109\/MetroAgriFor50201.2020.9277630"},{"key":"3218_CR163","doi-asserted-by":"crossref","unstructured":"Wang X, Bian Y, Qin X, Hu M, Xu B, Xie G (2020) Finite-time platoon control of connected and automated vehicles with mismatched disturbances. In: 2020 39th Chinese Control Conference (CCC). IEEE, pp. 5613\u20135618","DOI":"10.23919\/CCC50068.2020.9189484"},{"issue":"5","key":"3218_CR164","doi-asserted-by":"publisher","first-page":"1462","DOI":"10.3390\/rs4051462","volume":"4","author":"J Kelcey","year":"2012","unstructured":"Kelcey J, Lucieer A (2012) Sensor correction of a 6-band multispectral imaging sensor for uav remote sensing. Remote Sens 4(5):1462\u20131493","journal-title":"Remote Sens"},{"issue":"22","key":"3218_CR165","doi-asserted-by":"publisher","first-page":"8629","DOI":"10.3390\/s22228629","volume":"22","author":"Z Varga","year":"2022","unstructured":"Varga Z, V\u00f6r\u00f6s F, P\u00e1l M, Kov\u00e1cs B, Jung A, Elek I (2022) Performance and accuracy comparisons of classification methods and perspective solutions for uav-based near-real-time out of the lab data processing. Sensors 22(22):8629","journal-title":"Sensors"},{"key":"3218_CR166","doi-asserted-by":"crossref","unstructured":"Li J, Yan D, Wang G, Zhang L (2014) An improved sift algorithm for unmanned aerial vehicle imagery. In: IOP Conference Series: Earth and Environmental Science, vol. 17, pp. 012187. IOP Publishing","DOI":"10.1088\/1755-1315\/17\/1\/012187"},{"key":"3218_CR167","doi-asserted-by":"publisher","first-page":"21621","DOI":"10.1109\/ACCESS.2024.3363413","volume":"12","author":"M Muzammul","year":"2024","unstructured":"Muzammul M, Algarni A, Ghadi YY, Assam M (2024) Enhancing uav aerial image analysis: integrating advanced sahi techniques with real-time detection models on the visdrone dataset. IEEE Access 12:21621\u201321633","journal-title":"IEEE Access"},{"issue":"13","key":"3218_CR168","doi-asserted-by":"publisher","first-page":"11214","DOI":"10.1109\/JIOT.2021.3126329","volume":"9","author":"Y Wang","year":"2021","unstructured":"Wang Y, Chen M, Pan C, Wang K, Pan Y (2021) Joint optimization of uav trajectory and sensor uploading powers for uav-assisted data collection in wireless sensor networks. IEEE Internet Things J 9(13):11214\u201311226","journal-title":"IEEE Internet Things J"},{"key":"3218_CR169","doi-asserted-by":"crossref","unstructured":"Dang Y, Benza\u00efd C, Yang B, Taleb T (2021) Deep learning for gps spoofing detection in cellular-enabled uav systems. 2021 International Conference on Networking and Network Applications. IEEE, NaNA, pp. 501\u2013506","DOI":"10.1109\/NaNA53684.2021.00093"},{"issue":"7","key":"3218_CR170","doi-asserted-by":"publisher","first-page":"116","DOI":"10.3390\/agriculture8070116","volume":"8","author":"A Matese","year":"2018","unstructured":"Matese A, Di Gennaro SF (2018) Practical applications of a multisensor uav platform based on multispectral, thermal and rgb high resolution images in precision viticulture. Agriculture 8(7):116","journal-title":"Agriculture"},{"key":"3218_CR171","doi-asserted-by":"publisher","first-page":"371","DOI":"10.5194\/isprsarchives-XL-3-W3-371-2015","volume":"40","author":"W Tampubolon","year":"2015","unstructured":"Tampubolon W, Reinhardt W (2015) Uav data processing for rapid mapping activities. Int Arch Photogramm Remote Sens Spat Inf Sci 40:371\u2013377","journal-title":"Int Arch Photogramm Remote Sens Spat Inf Sci"},{"issue":"1","key":"3218_CR172","doi-asserted-by":"publisher","first-page":"2609","DOI":"10.1038\/s41598-024-53181-2","volume":"14","author":"Q Cheng","year":"2024","unstructured":"Cheng Q, Wang Y, He W, Bai Y (2024) Lightweight air-to-air unmanned aerial vehicle target detection model. Sci Rep 14(1):2609","journal-title":"Sci Rep"},{"key":"3218_CR173","doi-asserted-by":"publisher","first-page":"153","DOI":"10.5194\/isprsarchives-XL-5-W3-153-2013","volume":"40","author":"M Mangiameli","year":"2014","unstructured":"Mangiameli M, Mussumeci G (2014) Real time integration of field data into a gis platform for the management of hydrological emergencies. Int Arch Photogramm Remote Sens Spat Inf Sci 40:153\u2013158","journal-title":"Int Arch Photogramm Remote Sens Spat Inf Sci"},{"issue":"2","key":"3218_CR174","first-page":"49","volume":"1","author":"NQ Bui","year":"2020","unstructured":"Bui NQ, Le DH, Nguyen QL, Tong SS, Duong AQ, Pham VH, Phan TH, Pham TL (2020) Method of defining the parameters for uav point cloud classification algorithm. In\u017cynieria Mineralna 1(2):49\u201356","journal-title":"In\u017cynieria Mineralna"},{"issue":"11","key":"3218_CR175","doi-asserted-by":"publisher","first-page":"0260056","DOI":"10.1371\/journal.pone.0260056","volume":"16","author":"S Ahmed","year":"2021","unstructured":"Ahmed S, Nicholson CE, Muto P, Perry JJ, Dean JR (2021) Applied aerial spectroscopy: a case study on remote sensing of an ancient and semi-natural woodland. PLoS ONE 16(11):0260056","journal-title":"PLoS ONE"},{"issue":"7","key":"3218_CR176","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.3390\/rs14071633","volume":"14","author":"C Weber","year":"2022","unstructured":"Weber C, Eggert M, Rodrigo-Comino J, Udelhoven T (2022) Transforming 2d radar remote sensor information from a uav into a 3d world-view. Remote Sens 14(7):1633","journal-title":"Remote Sens"},{"key":"3218_CR177","doi-asserted-by":"publisher","first-page":"196","DOI":"10.15588\/1607-3274-2022-3-18","volume":"3","author":"O Fesenko","year":"2022","unstructured":"Fesenko O, Bieliakov R, Radzivilov H, Sasin S, Borysov O, Borysov I, Derkach T, Kovalchuk O (2022) Method of improving the accuracy of navigation mems data processing of uav inertial navigation system. Radio Electron Comput Sci Control 3:196\u2013196","journal-title":"Radio Electron Comput Sci Control"},{"issue":"10","key":"3218_CR178","doi-asserted-by":"publisher","first-page":"620","DOI":"10.3390\/drones7100620","volume":"7","author":"Z Cao","year":"2023","unstructured":"Cao Z, Kooistra L, Wang W, Guo L, Valente J (2023) Real-time object detection based on uav remote sensing: a systematic literature review. Drones 7(10):620","journal-title":"Drones"},{"issue":"7","key":"3218_CR179","doi-asserted-by":"publisher","first-page":"160","DOI":"10.3390\/drones6070160","volume":"6","author":"F Dadrass Javan","year":"2022","unstructured":"Dadrass Javan F, Samadzadegan F, Gholamshahi M, Ashatari Mahini F (2022) A modified yolov4 deep learning network for vision-based uav recognition. Drones 6(7):160","journal-title":"Drones"},{"issue":"1","key":"3218_CR180","doi-asserted-by":"publisher","first-page":"2","DOI":"10.3390\/rs15010002","volume":"15","author":"T Hong","year":"2022","unstructured":"Hong T, Liang H, Yang Q, Fang L, Kadoch M, Cheriet M (2022) A real-time tracking algorithm for multi-target uav based on deep learning. Remote Sens 15(1):2","journal-title":"Remote Sens"},{"issue":"1","key":"3218_CR181","doi-asserted-by":"publisher","first-page":"910","DOI":"10.1080\/17538947.2023.2187465","volume":"16","author":"F Huang","year":"2023","unstructured":"Huang F, Chen S, Wang Q, Chen Y, Zhang D (2023) Using deep learning in an embedded system for real-time target detection based on images from an unmanned aerial vehicle: Vehicle detection as a case study. Int J Digital Earth 16(1):910\u2013936","journal-title":"Int J Digital Earth"},{"key":"3218_CR182","doi-asserted-by":"crossref","unstructured":"Wang B, Kang H, Li J, Sun G, Sun Z, Wang J, Niyato D (2025) Uav-assisted joint mobile edge computing and data collection via matching-enabled deep reinforcement learning. IEEE Internet Things J","DOI":"10.1109\/JIOT.2025.3542025"},{"key":"3218_CR183","unstructured":"Zhang Z, Zeng C, Dhameliya M, Chowdhury S, Rai R (2020) Deep learning based multi-modal sensing for tracking and state extraction of small quadcopters. arXiv preprint arXiv:2012.04794"},{"key":"3218_CR184","doi-asserted-by":"crossref","unstructured":"Svanstr\u00f6m F, Englund C, Alonso-Fernandez F (2021) Real-time drone detection and tracking with visible, thermal and acoustic sensors. In: 2020 25th International Conference on Pattern Recognition (ICPR). IEEE, pp. 7265\u20137272","DOI":"10.1109\/ICPR48806.2021.9413241"},{"issue":"22","key":"3218_CR185","doi-asserted-by":"publisher","first-page":"2984","DOI":"10.3390\/math9222984","volume":"9","author":"GP Joshi","year":"2021","unstructured":"Joshi GP, Alenezi F, Thirumoorthy G, Dutta AK, You J (2021) Ensemble of deep learning-based multimodal remote sensing image classification model on unmanned aerial vehicle networks. Mathematics 9(22):2984","journal-title":"Mathematics"},{"issue":"18","key":"3218_CR186","doi-asserted-by":"publisher","first-page":"6791","DOI":"10.3390\/s22186791","volume":"22","author":"E Cinar","year":"2022","unstructured":"Cinar E (2022) A sensor fusion method using transfer learning models for equipment condition monitoring. Sensors 22(18):6791","journal-title":"Sensors"},{"issue":"15","key":"3218_CR187","doi-asserted-by":"publisher","first-page":"5800","DOI":"10.3390\/s22155800","volume":"22","author":"H Yin","year":"2022","unstructured":"Yin H, Li D, Wang Y, Hong X (2022) Adaptive data fusion method of multisensors based on lstm-gwfa hybrid model for tracking dynamic targets. Sensors 22(15):5800","journal-title":"Sensors"},{"key":"3218_CR188","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1590\/jatm.v13.1186","volume":"13","author":"A Alos","year":"2021","unstructured":"Alos A, Dahrouj Z (2021) Using multiple deep neural networks platform to detect different types of potential faults in unmanned aerial vehicles. J Aerosp Technol Manag 13:1321","journal-title":"J Aerosp Technol Manag"},{"key":"3218_CR189","doi-asserted-by":"crossref","unstructured":"Bell V, Rengasamy D, Rothwell B, Figueredo GP (2022) Anomaly detection for unmanned aerial vehicle sensor data using a stacked recurrent autoencoder method with dynamic thresholding. arXiv preprint arXiv:2203.04734","DOI":"10.4271\/01-15-02-0017"},{"issue":"5","key":"3218_CR190","doi-asserted-by":"publisher","first-page":"90","DOI":"10.3390\/jimaging7050090","volume":"7","author":"S Hamdi","year":"2021","unstructured":"Hamdi S, Bouindour S, Snoussi H, Wang T, Abid M (2021) End-to-end deep one-class learning for anomaly detection in uav video stream. J Imaging 7(5):90","journal-title":"J Imaging"},{"issue":"1","key":"3218_CR191","doi-asserted-by":"publisher","first-page":"2329260","DOI":"10.1080\/21642583.2024.2329260","volume":"12","author":"M Alali","year":"2024","unstructured":"Alali M, Kazeminajafabadi A, Imani M (2024) Deep reinforcement learning sensor scheduling for effective monitoring of dynamical systems. Syst Sci Control Eng 12(1):2329260","journal-title":"Syst Sci Control Eng"},{"key":"3218_CR192","doi-asserted-by":"publisher","first-page":"140041","DOI":"10.1109\/ACCESS.2023.3339581","volume":"11","author":"S Zhou","year":"2023","unstructured":"Zhou S, Han Y, Chen N, Huang S, Igorevich KK, Luo J, Zhang P (2023) Transformer-based discriminative and strong representation deep hashing for cross-modal retrieval. IEEE Access 11:140041\u2013140055. https:\/\/doi.org\/10.1109\/ACCESS.2023.3339581","journal-title":"IEEE Access"},{"issue":"24","key":"3218_CR193","doi-asserted-by":"publisher","first-page":"25150","DOI":"10.1109\/JIOT.2022.3195677","volume":"9","author":"OM Gul","year":"2022","unstructured":"Gul OM, Erkmen AM, Kantarci B (2022) Uav-driven sustainable and quality-aware data collection in robotic wireless sensor networks. IEEE Internet Things J 9(24):25150\u201325164. https:\/\/doi.org\/10.1109\/JIOT.2022.3195677","journal-title":"IEEE Internet Things J"},{"issue":"4","key":"3218_CR194","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MCOMSTD.0001.2000039","volume":"5","author":"M Aloqaily","year":"2021","unstructured":"Aloqaily M, Jararweh Y, Bouachir O (2021) Trustworthy cooperative uav-based data management in densely crowded environments. IEEE Commun Stand Mag 5(4):18\u201324. https:\/\/doi.org\/10.1109\/MCOMSTD.0001.2000039","journal-title":"IEEE Commun Stand Mag"},{"issue":"21","key":"3218_CR195","doi-asserted-by":"publisher","first-page":"2603","DOI":"10.3390\/electronics10212603","volume":"10","author":"MT Nguyen","year":"2021","unstructured":"Nguyen MT, Nguyen CV, Do HT, Hua HT, Tran TA, Nguyen AD, Ala G, Viola F (2021) Uav-assisted data collection in wireless sensor networks: a comprehensive survey. Electronics 10(21):2603","journal-title":"Electronics"},{"issue":"17","key":"3218_CR196","doi-asserted-by":"publisher","first-page":"3664","DOI":"10.3390\/electronics12173664","volume":"12","author":"X Zhai","year":"2023","unstructured":"Zhai X, Huang Z, Li T, Liu H, Wang S (2023) Yolo-drone: an optimized yolov8 network for tiny uav object detection. Electronics 12(17):3664","journal-title":"Electronics"},{"issue":"1","key":"3218_CR197","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1109\/TVT.2022.3203704","volume":"72","author":"Y Zeng","year":"2023","unstructured":"Zeng Y, Tang J (2023) Mec-assisted real-time data acquisition and processing for uav with general missions. IEEE Trans Veh Technol 72(1):1058\u20131072. https:\/\/doi.org\/10.1109\/TVT.2022.3203704","journal-title":"IEEE Trans Veh Technol"},{"issue":"2","key":"3218_CR198","doi-asserted-by":"publisher","first-page":"89","DOI":"10.3390\/drones7020089","volume":"7","author":"MY Arafat","year":"2023","unstructured":"Arafat MY, Alam MM, Moh S (2023) Vision-based navigation techniques for unmanned aerial vehicles: review and challenges. Drones 7(2):89","journal-title":"Drones"},{"key":"3218_CR199","doi-asserted-by":"publisher","first-page":"2815","DOI":"10.1109\/OJCOMS.2024.3392623","volume":"5","author":"H Shakhatreh","year":"2024","unstructured":"Shakhatreh H, Sawalmeh A, Hayajneh KF, Abdel-Razeq S, Malkawi W, Al-Fuqaha A (2024) A systematic review of interference mitigation techniques in current and future uav-assisted wireless networks. IEEE Open J Commun Soc 5:2815\u20132846. https:\/\/doi.org\/10.1109\/OJCOMS.2024.3392623","journal-title":"IEEE Open J Commun Soc"},{"key":"3218_CR200","doi-asserted-by":"publisher","first-page":"139069","DOI":"10.1109\/ACCESS.2023.3338377","volume":"11","author":"G Ahmed","year":"2023","unstructured":"Ahmed G, Sheltami TR (2023) A safety system for maximizing operated uavs capacity under regulation constraints. IEEE Access 11:139069\u2013139081. https:\/\/doi.org\/10.1109\/ACCESS.2023.3338377","journal-title":"IEEE Access"},{"issue":"4","key":"3218_CR201","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1109\/MCOMSTD.0001.2000074","volume":"5","author":"AM Vegni","year":"2021","unstructured":"Vegni AM, Loscri V, Calafate CT, Manzoni P (2021) Communication technologies enabling effective uav networks: a standards perspective. IEEE Commun Stand Mag 5(4):33\u201340. https:\/\/doi.org\/10.1109\/MCOMSTD.0001.2000074","journal-title":"IEEE Commun Stand Mag"},{"key":"3218_CR202","doi-asserted-by":"publisher","first-page":"14463","DOI":"10.1109\/ACCESS.2022.3145199","volume":"10","author":"R Alkadi","year":"2022","unstructured":"Alkadi R, Alnuaimi N, Yeun CY, Shoufan A (2022) Blockchain interoperability in unmanned aerial vehicles networks: state-of-the-art and open issues. IEEE Access 10:14463\u201314479. https:\/\/doi.org\/10.1109\/ACCESS.2022.3145199","journal-title":"IEEE Access"},{"key":"3218_CR203","doi-asserted-by":"publisher","first-page":"8085","DOI":"10.1109\/JSTARS.2022.3206399","volume":"15","author":"W Liu","year":"2022","unstructured":"Liu W, Quijano K, Crawford MM (2022) Yolov5-tassel: Detecting tassels in rgb uav imagery with improved yolov5 based on transfer learning. IEEE J Select Top Appl Earth Observ Remote Sens 15:8085\u20138094","journal-title":"IEEE J Select Top Appl Earth Observ Remote Sens"},{"key":"3218_CR204","doi-asserted-by":"publisher","first-page":"113049","DOI":"10.1109\/ACCESS.2024.3440064","volume":"12","author":"OY Al-Jarrah","year":"2024","unstructured":"Al-Jarrah OY, Shatnawi AS, Shurman MM, Ramadan OA, Muhaidat S (2024) Exploring deep learning-based visual localization techniques for uavs in gps-denied environments. IEEE Access 12:113049\u2013113071","journal-title":"IEEE Access"}],"container-title":["International Journal of Machine Learning and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-026-03218-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s13042-026-03218-x","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s13042-026-03218-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T10:03:34Z","timestamp":1788170614000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s13042-026-03218-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,13]]},"references-count":204,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,8]]}},"alternative-id":["3218"],"URL":"https:\/\/doi.org\/10.1007\/s13042-026-03218-x","relation":{},"ISSN":["1868-8071","1868-808X"],"issn-type":[{"value":"1868-8071","type":"print"},{"value":"1868-808X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,13]]},"assertion":[{"value":"7 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 July 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no conflict of interest.","order":1,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"383"}}