{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T16:32:46Z","timestamp":1774369966616,"version":"3.50.1"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T00:00:00Z","timestamp":1748217600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T00:00:00Z","timestamp":1748217600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/100014718","name":"Innovative Research Group Project of the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["No.62303231"],"award-info":[{"award-number":["No.62303231"]}],"id":[{"id":"10.13039\/100014718","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013156","name":"Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology","doi-asserted-by":"publisher","award":["No.2024r058"],"award-info":[{"award-number":["No.2024r058"]}],"id":[{"id":"10.13039\/501100013156","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Complex Intell. Syst."],"published-print":{"date-parts":[[2025,7]]},"DOI":"10.1007\/s40747-025-01875-z","type":"journal-article","created":{"date-parts":[[2025,5,26]],"date-time":"2025-05-26T06:55:47Z","timestamp":1748242547000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["RTL-Net: real-time lightweight Urban traffic object detection algorithm"],"prefix":"10.1007","volume":"11","author":[{"given":"Zhiqing","family":"Cui","sequence":"first","affiliation":[]},{"given":"Jiahao","family":"Yuan","sequence":"additional","affiliation":[]},{"given":"Haibin","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Yamei","family":"Wei","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1843-8567","authenticated-orcid":false,"given":"Zhenglong","family":"Ding","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,26]]},"reference":[{"issue":"5","key":"1875_CR1","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.1007\/s11263-019-01186-0","volume":"128","author":"S Hu","year":"2020","unstructured":"Hu S, Lee GH (2020) Image-based geo-localization using satellite imagery. Int J Comput Vis 128(5):1205\u20131219","journal-title":"Int J Comput Vis"},{"key":"1875_CR2","unstructured":"Campbell J.\u00a0B, Wynne R.\u00a0H (2011), Introduction to remote sensing. Guilford press,"},{"key":"1875_CR3","doi-asserted-by":"crossref","unstructured":"Chen S, Kang Q, Wang Z, Shen Z, Pu H, Han H, Gu Z (2017), Target detection method by airborne and spaceborne images fusion based on past images, in LIDAR Imaging Detection and Target Recognition 2017, vol. 10605.SPIE, , pp. 686\u2013696","DOI":"10.1117\/12.2293925"},{"key":"1875_CR4","doi-asserted-by":"crossref","unstructured":"Shuxin L, Zhilong Z,Biao L (2018), A plane target detection algorithm in remote sensing images based on deep learning network technology, in Journal of Physics: Conference Series, vol. 960, no.\u00a01. IOP Publishing, p. 012025","DOI":"10.1088\/1742-6596\/960\/1\/012025"},{"key":"1875_CR5","doi-asserted-by":"publisher","first-page":"3735","DOI":"10.1109\/JSTARS.2020.3005403","volume":"13","author":"G Cheng","year":"2020","unstructured":"Cheng G, Xie X, Han J, Guo L, Xia G-S (2020) Remote sensing image scene classification meets deep learning: challenges, methods, benchmarks, and opportunities. IEEE J Selected Topics Appl Earth Obs Remote Sens 13:3735\u20133756","journal-title":"IEEE J Selected Topics Appl Earth Obs Remote Sens"},{"issue":"6","key":"1875_CR6","doi-asserted-by":"publisher","first-page":"1312","DOI":"10.3390\/electronics12061312","volume":"12","author":"M Ju","year":"2023","unstructured":"Ju M, Niu B, Jin S, Liu Z (2023) Superdet: an efficient single-shot network for vehicle detection in remote sensing images. Electronics 12(6):1312","journal-title":"Electronics"},{"issue":"11","key":"1875_CR7","doi-asserted-by":"publisher","first-page":"6047","DOI":"10.1109\/TNNLS.2021.3080276","volume":"33","author":"A Bouguettaya","year":"2021","unstructured":"Bouguettaya A, Zarzour H, Kechida A, Taberkit AM (2021) Vehicle detection from uav imagery with deep learning: A review. IEEE Trans Neural Netw Learn Syst 33(11):6047\u20136067","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"key":"1875_CR8","doi-asserted-by":"crossref","unstructured":"Redmon J, Divvala S, Girshick R, Farhadi A (2016), You only look once: Unified, real-time object detection, in Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 779\u2013788","DOI":"10.1109\/CVPR.2016.91"},{"issue":"6","key":"1875_CR9","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"Ren S, He K, Girshick R, Sun J (2016) Faster r-cnn: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1875_CR10","unstructured":"Girshick R (2015), Proc. of the ieee int. conf. on comput. vision, in Proc. IEEE Int. Conf. Comput. Vision,"},{"key":"1875_CR11","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu C.-Y, Berg A.\u00a0C (2016), Ssd: Single shot multibox detector, in Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11\u201314, 2016, Proceedings, Part I 14.Springer, pp. 21\u201337","DOI":"10.1007\/978-3-319-46448-0_2"},{"issue":"9","key":"1875_CR12","doi-asserted-by":"publisher","first-page":"7933","DOI":"10.1109\/TGRS.2020.3048384","volume":"59","author":"E Liu","year":"2021","unstructured":"Liu E, Zheng Y, Pan B, Xu X, Shi Z (2021) Dcl-net: Augmenting the capability of classification and localization for remote sensing object detection. IEEE Trans Geosci Remote Sens 59(9):7933\u20137944","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"19","key":"1875_CR13","doi-asserted-by":"publisher","first-page":"3215","DOI":"10.3390\/electronics11193215","volume":"11","author":"J Dai","year":"2022","unstructured":"Dai J, Li T, Xuan Z, Feng Z (2022) Automated defect analysis system for industrial computerized tomography images of solid rocket motor grains based on yolo-v4 model. Electronics 11(19):3215","journal-title":"Electronics"},{"issue":"10","key":"1875_CR14","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/ad633d","volume":"35","author":"H Tao","year":"2024","unstructured":"Tao H, Zheng Y, Wang Y, Qiu J, Stojanovic V (2024) Enhanced feature extraction YOLO industrial small object detection algorithm based on receptive-field attention and multi-scale features. Measurement Sci Technol 35(10):105023","journal-title":"Measurement Sci Technol"},{"issue":"4","key":"1875_CR15","doi-asserted-by":"publisher","DOI":"10.1088\/1361-6501\/acb075","volume":"34","author":"L Shen","year":"2023","unstructured":"Shen L, Tao H, Ni Y, Wang Y, Stojanovic V (2023) Improved YOLOv3 model with feature map cropping for multi-scale road object detection. Measure Sci Technol 34(4):045406","journal-title":"Measure Sci Technol"},{"issue":"10","key":"1875_CR16","doi-asserted-by":"publisher","first-page":"1943","DOI":"10.1177\/01423312231225782","volume":"46","author":"Y Tao","year":"2024","unstructured":"Tao Y, Tao H, Zhuang Z, Stojanovic V, Paszke W (2024) Quantized iterative learning control of communication-constrained systems with encoding and decoding mechanism. Trans Inst Measurement Control 46(10):1943\u20131954","journal-title":"Trans Inst Measurement Control"},{"issue":"6","key":"1875_CR17","doi-asserted-by":"publisher","first-page":"3255","DOI":"10.3390\/s23063255","volume":"23","author":"H-C Nguyen","year":"2023","unstructured":"Nguyen H-C, Nguyen T-H, Scherer R, Le V-H (2023) Yolo series for human hand action detection and classification from egocentric videos. Sensors 23(6):3255","journal-title":"Sensors"},{"key":"1875_CR18","unstructured":"Chandana R,Ramachandra A (2022), Real time object detection system with yolo and cnn models: a review, arXiv:2208, vol. 773,"},{"key":"1875_CR19","first-page":"1","volume":"19","author":"J Li","year":"2021","unstructured":"Li J, Zhang Z, Tian Y, Xu Y, Wen Y, Wang S (2021) Target-guided feature super-resolution for vehicle detection in remote sensing images. IEEE Geosci Remote Sens Lett 19:1\u20135","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"1875_CR20","doi-asserted-by":"publisher","first-page":"4730","DOI":"10.1109\/JSTARS.2022.3181594","volume":"15","author":"P Gao","year":"2022","unstructured":"Gao P, Tian T, Zhao T, Li L, Zhang N, Tian J (2022) Double fcos: A two-stage model utilizing fcos for vehicle detection in various remote sensing scenes. IEEE J Selected Topics Appl Earth Obs Remote Sens 15:4730\u20134743","journal-title":"IEEE J Selected Topics Appl Earth Obs Remote Sens"},{"issue":"13","key":"1875_CR21","doi-asserted-by":"publisher","first-page":"10397","DOI":"10.3390\/su151310397","volume":"15","author":"D Guo","year":"2023","unstructured":"Guo D, Wang Y, Zhu S, Li X (2023) A vehicle detection method based on an improved u-yolo network for high-resolution remote-sensing images. Sustainability 15(13):10397","journal-title":"Sustainability"},{"key":"1875_CR22","doi-asserted-by":"crossref","unstructured":"Ma C, Fu Y, Wang D, Guo R, Zhao X, Fang J (2023), Yolo-uav: Object detection method of unmanned aerial vehicle imagery based on efficient multi-scale feature fusion, IEEE Access,","DOI":"10.1109\/ACCESS.2023.3329713"},{"issue":"2","key":"1875_CR23","doi-asserted-by":"publisher","first-page":"95","DOI":"10.3390\/drones7020095","volume":"7","author":"Q Cheng","year":"2023","unstructured":"Cheng Q, Wang H, Zhu B, Shi Y, Xie B (2023) A real-time uav target detection algorithm based on edge computing. Drones 7(2):95","journal-title":"Drones"},{"issue":"1","key":"1875_CR24","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.32604\/cmc.2023.034876","volume":"75","author":"P Zhang","year":"2023","unstructured":"Zhang P, Deng H, Chen Z (2023) Rt-yolo: a residual feature fusion triple attention network for aerial image target detection. Comput Mater Continua 75(1):1411\u20131430","journal-title":"Comput Mater Continua"},{"issue":"6","key":"1875_CR25","doi-asserted-by":"publisher","first-page":"3049","DOI":"10.1007\/s00521-023-09133-4","volume":"36","author":"K Su","year":"2024","unstructured":"Su K, Cao L, Zhao B, Li N, Wu D, Han X (2024) N-iou: better iou-based bounding box regression loss for object detection. Neural Comput Appl 36(6):3049\u20133063","journal-title":"Neural Comput Appl"},{"key":"1875_CR26","first-page":"1","volume":"20","author":"M Cui","year":"2023","unstructured":"Cui M, Duan Y, Pan C, Wang J, Liu H (2023) Optimization for anchor-free object detection via scale-independent giou loss. IEEE Geosci Remote Sens Lett 20:1\u20135","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"1875_CR27","doi-asserted-by":"crossref","unstructured":"Liu Z, Cheng J, Wang Q, Xian L (2022), Improved design based on iou loss functions for bounding box regression, in, IEEE 6th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC). IEEE 2022:452\u2013458","DOI":"10.1109\/IAEAC54830.2022.9929938"},{"key":"1875_CR28","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1016\/j.neunet.2023.11.041","volume":"170","author":"C Liu","year":"2024","unstructured":"Liu C, Wang K, Li Q, Zhao F, Zhao K, Ma H (2024) Powerful-iou: More straightforward and faster bounding box regression loss with a nonmonotonic focusing mechanism. Neural Netw 170:276\u2013284","journal-title":"Neural Netw"},{"key":"1875_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2021.103107","volume":"77","author":"Z Li","year":"2021","unstructured":"Li Z, Hu C, Nai K, Yuan J (2021) Siamese target estimation network with aiou loss for real-time visual tracking. J Vis Commun Image Represent 77:103107","journal-title":"J Vis Commun Image Represent"},{"key":"1875_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2019.104948","volume":"165","author":"K Kamal","year":"2019","unstructured":"Kamal K, Yin Z, Wu M, Wu Z (2019) Depthwise separable convolution architectures for plant disease classification. Comput Electron Agricult 165:104948","journal-title":"Comput Electron Agricult"},{"key":"1875_CR31","unstructured":"Wei H, Liu X, Xu S, Dai Z, Dai Y, Xu X (2022), Dwrseg: Rethinking efficient acquisition of multi-scale contextual information for real-time semantic segmentation, arXiv preprint arXiv:2212.01173,"},{"key":"1875_CR32","doi-asserted-by":"crossref","unstructured":"Tan M, Pang R, Le Q.\u00a0V (2020), Efficientdet: Scalable and efficient object detection, in Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, 10\u00a0781\u201310\u00a0790","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"1875_CR33","doi-asserted-by":"crossref","unstructured":"Zhang H, Du Q, Qi Q, Zhang J, Wang F, Gao M (2023), A recursive attention-enhanced bidirectional feature pyramid network for small object detection, Multimedia tools and applications, vol.\u00a082, no.\u00a09, pp. 13\u00a0999\u201314\u00a0018,","DOI":"10.1007\/s11042-022-13951-4"},{"key":"1875_CR34","doi-asserted-by":"crossref","unstructured":"Chen J, Mai H, Luo L, Chen X, Wu K (2021), Effective feature fusion network in bifpn for small object detection, in 2021 IEEE international conference on image processing (ICIP).IEEE, pp. 699\u2013703","DOI":"10.1109\/ICIP42928.2021.9506347"},{"issue":"11","key":"1875_CR35","doi-asserted-by":"publisher","first-page":"7380","DOI":"10.1109\/TPAMI.2021.3119563","volume":"44","author":"P Zhu","year":"2021","unstructured":"Zhu P, Wen L, Du D, Bian X, Fan H, Hu Q, Ling H (2021) Detection and tracking meet drones challenge. IEEE Trans Pattern Anal Mach Intell 44(11):7380\u20137399","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"1875_CR36","doi-asserted-by":"crossref","unstructured":"Du D,Zhu P, Wen L, Bian X, Lin H, Hu Q, Peng T, Zheng J, Wang X, Zhang Y et\u00a0al. (2019), Visdrone-det2019: The vision meets drone object detection in image challenge results, in Proceedings of the IEEE\/CVF international conference on computer vision workshops, pp. 0\u20130","DOI":"10.1109\/ICCVW.2019.00031"},{"key":"1875_CR37","doi-asserted-by":"crossref","unstructured":"Lin H.-Y, Tu K.-C, Li C.-Y (2020), Vaid: An aerial image dataset for vehicle detection and classification, IEEE Access, vol.\u00a08, pp. 212\u00a0209\u2013212\u00a0219,","DOI":"10.1109\/ACCESS.2020.3040290"},{"key":"1875_CR38","unstructured":"Carrasco D.\u00a0P, Rashwan H.\u00a0A, Garc\u00eda M.\u00a0\u00c1, Puig D (2021), T-yolo: Tiny vehicle detection based on yolo and multi-scale convolutional neural networks, Ieee Access, vol.\u00a011, pp. 22\u00a0430\u201322\u00a0440,"},{"issue":"2","key":"1875_CR39","doi-asserted-by":"publisher","first-page":"4296","DOI":"10.1080\/15567036.2022.2074174","volume":"44","author":"L Chen","year":"2022","unstructured":"Chen L, Huang H, Tang P, Yao D, Yang H, Ghadimi N (2022) Optimal modeling of combined cooling, heating, and power systems using developed African vulture optimization: a case study in watersport complex. Energy Sources Part A 44(2):4296\u20134317","journal-title":"Energy Sources Part A"},{"key":"1875_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2022.105311","volume":"55","author":"W Jiang","year":"2022","unstructured":"Jiang W, Wang X, Huang H, Zhang D, Ghadimi N (2022) Optimal economic scheduling of microgrids considering renewable energy sources based on energy hub model using demand response and improved water wave optimization algorithm. J Energy Storage 55:105311","journal-title":"J Energy Storage"},{"key":"1875_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.csite.2024.104005","volume":"54","author":"S Li","year":"2024","unstructured":"Li S, Fang X, Liao J, Ghadamyari M, Khayatnezhad M, Ghadimi N (2024) Evaluating the efficiency of cchp systems in xinjiang uygur autonomous region: an optimal strategy based on improved mother optimization algorithm. Case Stud Thermal Eng 54:104005","journal-title":"Case Stud Thermal Eng"},{"key":"1875_CR42","volume":"52","author":"E Han","year":"2022","unstructured":"Han E, Ghadimi N (2022) Model identification of proton-exchange membrane fuel cells based on a hybrid convolutional neural network and extreme learning machine optimized by improved honey badger algorithm. Sustain Energy Technol Assess 52:102005","journal-title":"Sustain Energy Technol Assess"},{"key":"1875_CR43","doi-asserted-by":"crossref","unstructured":"Kumar A (2024), Geo-tagged 3D geometric modeling of urban structures by mitigating reflected GPS signals using a laser range sensor, in Science and Information Conference, ser. SAI 2024. London: Springer, pp. 396\u2013414","DOI":"10.1007\/978-3-031-62281-6_29"},{"key":"1875_CR44","doi-asserted-by":"publisher","first-page":"164","DOI":"10.37394\/23208.2023.20.12","volume":"20","author":"AK Aggarwal","year":"2023","unstructured":"Aggarwal AK (2023) A review on genomics data analysis using machine learning. WSEAS Trans Biol Biomed 20:164\u2013175","journal-title":"WSEAS Trans Biol Biomed"},{"issue":"4","key":"1875_CR45","doi-asserted-by":"publisher","first-page":"3953","DOI":"10.1109\/TASE.2022.3141248","volume":"19","author":"RNA Algburi","year":"2022","unstructured":"Algburi RNA, Gao H, Al-Huda Z (2022) Improvement of an industrial robotic flaw detection system. IEEE Trans Auto Sci Eng 19(4):3953\u20133967","journal-title":"IEEE Trans Auto Sci Eng"},{"issue":"10","key":"1875_CR46","doi-asserted-by":"publisher","first-page":"7565","DOI":"10.1007\/s00521-021-06848-0","volume":"34","author":"RNA Algburi","year":"2022","unstructured":"Algburi RNA, Gao H, AlHuda Z (2022) A new synergy of singular spectrum analysis with a conscious algorithm to detect faults in industrial robotics. Neural Comput Appl 34(10):7565\u20137580","journal-title":"Neural Comput Appl"},{"key":"1875_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.108490","volume":"105","author":"S-J Ji","year":"2023","unstructured":"Ji S-J, Ling Q-H, Han F (2023) An improved algorithm for small object detection based on yolo v4 and multi-scale contextual information. Comput Electr Eng 105:108490","journal-title":"Comput Electr Eng"},{"key":"1875_CR48","doi-asserted-by":"crossref","unstructured":"Han Y, Wang J, Lu L (2019), A typical remote sensing object detection method based on yolov3, in 2019 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE).IEEE, pp. 520\u20135203","DOI":"10.1109\/ICMCCE48743.2019.00121"},{"issue":"6","key":"1875_CR49","doi-asserted-by":"publisher","first-page":"8095","DOI":"10.1007\/s40747-024-01580-3","volume":"10","author":"L Zhang","year":"2024","unstructured":"Zhang L, Huang ZA, Shi C et al (2024) Mfpidet: improved yolov7 architecture based on multi-scale feature fusion for prohibited item detection in complex environment. Complex Intell Syst 10(6):8095\u20138108","journal-title":"Complex Intell Syst"},{"key":"1875_CR50","unstructured":"Cao H, Chen G, Li Z,Lin J, Knoll A (2021), Lightweight convolutional neural network with gaussian-based grasping representation for robotic grasping detection, arXiv preprint arXiv:2101.10226,"},{"key":"1875_CR51","doi-asserted-by":"crossref","unstructured":"Yi H, Liu B, Zhao B,Liu E (2023), Small object detection algorithm based on improved yolov8 for remote sensing, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","DOI":"10.1109\/JSTARS.2023.3339235"},{"key":"1875_CR52","doi-asserted-by":"crossref","unstructured":"Fan X, Hu Z, Zhao Y, Chen J, Wei T, Huang Z (2024), A small ship object detection method for satellite remote sensing data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","DOI":"10.1109\/JSTARS.2024.3419786"},{"key":"1875_CR53","doi-asserted-by":"crossref","unstructured":"Zhou Q, Shi H, Xiang W, Kang B, Latecki L.\u00a0J (2024), Dpnet: Dual-path network for real-time object detection with lightweight attention, IEEE Transactions on Neural Networks and Learning Systems","DOI":"10.1109\/TNNLS.2024.3376563"},{"key":"1875_CR54","doi-asserted-by":"crossref","unstructured":"Wang Y, Zheng Y, Chen L et\u00a0al. (2024), Dib-uap: enhancing the transferability of universal adversarial perturbation via deep information bottleneck, Complex & Intelligent Systems, pp. 1\u201313","DOI":"10.1007\/s40747-024-01522-z"},{"key":"1875_CR55","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2023.3334492","volume":"61","author":"Y Liu","year":"2023","unstructured":"Liu Y, Xiong Z, Yuan Y, Wang Q (2023) Distilling knowledge from super-resolution for efficient remote sensing salient object detection. IEEE Trans Geosci Remote Sens 61:1\u201316","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"1875_CR56","doi-asserted-by":"crossref","unstructured":"Zhang C, Su J, Ju Y, Lam K.-M, Wang Q (2023). Efficient inductive vision transformer for oriented object detection in remote sensing imagery, IEEE Transactions on Geoscience and Remote Sensing","DOI":"10.1109\/TGRS.2023.3292418"},{"issue":"1","key":"1875_CR57","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1049\/stg2.12095","volume":"6","author":"M Ghiasi","year":"2023","unstructured":"Ghiasi M, Wang Z, Mehrandezh M, Jalilian S, Ghadimi N (2023) Evolution of smart grids towards the Internet of energy: concept and essential components for deep decarbonisation. IET Smart Grid 6(1):86\u2013102","journal-title":"IET Smart Grid"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-01875-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-025-01875-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-025-01875-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T11:08:07Z","timestamp":1750331287000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-025-01875-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,26]]},"references-count":57,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2025,7]]}},"alternative-id":["1875"],"URL":"https:\/\/doi.org\/10.1007\/s40747-025-01875-z","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,26]]},"assertion":[{"value":"13 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 March 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 May 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"304"}}