{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T08:59:13Z","timestamp":1774947553467,"version":"3.50.1"},"reference-count":54,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T00:00:00Z","timestamp":1736899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62163007"],"award-info":[{"award-number":["62163007"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62373116"],"award-info":[{"award-number":["62373116"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004001","name":"Guizhou Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["QKHZC[2023]118"],"award-info":[{"award-number":["QKHZC[2023]118"]}],"id":[{"id":"10.13039\/501100004001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004001","name":"Guizhou Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["QKHZC[2023]366"],"award-info":[{"award-number":["QKHZC[2023]366"]}],"id":[{"id":"10.13039\/501100004001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004001","name":"Guizhou Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["QKHZC[2024]005"],"award-info":[{"award-number":["QKHZC[2024]005"]}],"id":[{"id":"10.13039\/501100004001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004001","name":"Guizhou Provincial Science and Technology Department","doi-asserted-by":"publisher","award":["PTRC[2020]6007-2"],"award-info":[{"award-number":["PTRC[2020]6007-2"]}],"id":[{"id":"10.13039\/501100004001","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":[[2025,2]]},"DOI":"10.1007\/s40747-024-01776-7","type":"journal-article","created":{"date-parts":[[2025,1,15]],"date-time":"2025-01-15T08:48:22Z","timestamp":1736930902000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["View adaptive multi-object tracking method based on depth relationship cues"],"prefix":"10.1007","volume":"11","author":[{"given":"Haoran","family":"Sun","sequence":"first","affiliation":[]},{"given":"Yang","family":"Li","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8761-5195","authenticated-orcid":false,"given":"Guanci","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Zhidong","family":"Su","sequence":"additional","affiliation":[]},{"given":"Kexin","family":"Luo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,15]]},"reference":[{"key":"1776_CR1","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1016\/j.inffus.2022.10.015","volume":"91","author":"Y Li","year":"2023","unstructured":"Li Y, Yang G, Su Z, Li S, Wang Y (2023) Human activity recognition based on multienvironment sensor data. Inform Fusion 91:47\u201363","journal-title":"Inform Fusion"},{"key":"1776_CR2","doi-asserted-by":"publisher","first-page":"1145","DOI":"10.3233\/SHTI240612","volume":"316","author":"SF Abbasi","year":"2024","unstructured":"Abbasi SF, Bilal M, Mukherjee T, Churm J, Pournik O, Epiphaniou G, Arvanitis TN (2024) Deep learning-based synthetic skin lesion image classification. Stud Health Technol Inform 316:1145\u20131150. https:\/\/doi.org\/10.3233\/SHTI240612","journal-title":"Stud Health Technol Inform"},{"key":"1776_CR3","doi-asserted-by":"publisher","first-page":"1674","DOI":"10.3233\/SHTI240745","volume":"316","author":"T Mukherjee","year":"2024","unstructured":"Mukherjee T, Gour S, Abbasi SF, Pournik O, Arvanitis TN (2024) Development of a CNN for adult brain tumour characterisation: implications and future directions for transfer learning. Stud Health Technol Inform 316:1674\u20131678. https:\/\/doi.org\/10.3233\/SHTI240745","journal-title":"Stud Health Technol Inform"},{"issue":"1","key":"1776_CR4","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1007\/s40747-024-01610-0","volume":"11","author":"M Wang","year":"2024","unstructured":"Wang M, Yang G, Luo K, Li Y, He L (2024) Early stroke behavior detection based on improved video masked autoencoders for potential patients. Complex Intell Syst 11(1):30. https:\/\/doi.org\/10.1007\/s40747-024-01610-0","journal-title":"Complex Intell Syst"},{"issue":"1","key":"1776_CR5","doi-asserted-by":"publisher","first-page":"14697","DOI":"10.1038\/s41598-024-65545-9","volume":"14","author":"H Li","year":"2024","unstructured":"Li H, Yan S, Fu Y (2024) Data-fusion for in-situ monitoring and molten state identification during LPBF of NiCoCr medium-entropy alloy. Sci Rep-UK 14(1):14697. https:\/\/doi.org\/10.1038\/s41598-024-65545-9","journal-title":"Sci Rep-UK"},{"key":"1776_CR6","doi-asserted-by":"crossref","unstructured":"ElTobgui R, Zayer F, Iacoponi S, de Masi G, Renda F, Dias J (2024) Towards efficient underwater robotic swarms: edge-based comparative analysis of multi-object trackers. Oceans 2024 \u2013 Singapore, pp 1\u20137","DOI":"10.1109\/OCEANS51537.2024.10682269"},{"key":"1776_CR7","doi-asserted-by":"publisher","DOI":"10.4108\/airo.v2i1.3181","author":"AJ Moshayedi","year":"2023","unstructured":"Moshayedi AJ, Reza KS, Khan AS, Nawaz A (2023) Integrating virtual reality and robotic operation system (ROS) for AGV navigation. EAI Endorsed Trans AI Robot. https:\/\/doi.org\/10.4108\/airo.v2i1.3181","journal-title":"EAI Endorsed Trans AI Robot"},{"issue":"17","key":"1776_CR8","doi-asserted-by":"publisher","first-page":"5756","DOI":"10.3390\/s24175756","volume":"24","author":"Y Li","year":"2024","unstructured":"Li Y, Zhang B, Liu Y, Wang H, Zhang S (2024) personnel monitoring in shipboard surveillance using improved multi-object detection and tracking algorithm. Sensors-Basel 24(17):5756. https:\/\/doi.org\/10.3390\/s24175756","journal-title":"Sensors-Basel"},{"issue":"11","key":"1776_CR9","doi-asserted-by":"publisher","first-page":"7380","DOI":"10.1109\/TPAMI.2021.3119563","volume":"44","author":"PF Zhu","year":"2022","unstructured":"Zhu PF, Wen LY, Du DW, Bian X, Fan H, Hu QH, Ling HB (2022) Detection and tracking meet drones challenge. IEEE Trans Pattern Anal 44(11):7380\u20137399. https:\/\/doi.org\/10.1109\/TPAMI.2021.3119563","journal-title":"IEEE Trans Pattern Anal"},{"key":"1776_CR10","doi-asserted-by":"crossref","unstructured":"Zarei M, Moshayedi AJ, Zhong Y, Khan A, Kolahdooz A, Andani ME (2023) Indoor UAV object detection algorithms on three processors: implementation test and comparison. In: 2023 3rd international conference on consumer electronics and computer engineering (ICCECE), pp 812\u2013819","DOI":"10.1109\/ICCECE58074.2023.10135199"},{"key":"1776_CR11","doi-asserted-by":"crossref","unstructured":"Bewley A, Ge Z, Ott L, Ramos FT, Upcroft B (2016) Simple online and realtime tracking. In: 2016 IEEE international conference on image processing (ICIP), pp 3464\u20133468","DOI":"10.1109\/ICIP.2016.7533003"},{"key":"1776_CR12","doi-asserted-by":"crossref","unstructured":"Wojke N, Bewley A, Paulus D (2017) Simple online and realtime tracking with a deep association metric. In: 2017 IEEE international conference on image processing (ICIP), pp 3645\u20133649","DOI":"10.1109\/ICIP.2017.8296962"},{"key":"1776_CR13","doi-asserted-by":"crossref","unstructured":"Maggiolino G, Ahmad A, Cao J, Kitani K (2023) Deep OC-sort: multi-pedestrian tracking by adaptive re-identification. In: 2023 IEEE international conference on image processing (ICIP), pp 3025\u20133029","DOI":"10.1109\/ICIP49359.2023.10222576"},{"key":"1776_CR14","doi-asserted-by":"publisher","first-page":"8725","DOI":"10.1109\/TMM.2023.3240881","volume":"25","author":"Y Du","year":"2023","unstructured":"Du Y, Zhao Z, Song Y, Zhao Y, Su F, Gong T, Meng H (2023) StrongSORT: make DeepSORT great again. IEEE Trans Multimedia 25:8725\u20138737. https:\/\/doi.org\/10.1109\/TMM.2023.3240881","journal-title":"IEEE Trans Multimedia"},{"issue":"3","key":"1776_CR15","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s00138-024-01531-5","volume":"35","author":"VD Stanojevic","year":"2024","unstructured":"Stanojevic VD, Todorovic BT (2024) BoostTrack: boosting the similarity measure and detection confidence for improved multiple object tracking. Mach Vis Appl 35(3):53. https:\/\/doi.org\/10.1007\/s00138-024-01531-5","journal-title":"Mach Vis Appl"},{"key":"1776_CR16","unstructured":"Ge Z, Liu S, Wang F, Li Z, Sun J (2021) YOLOX: Exceeding YOLO series in 2021. ArXiv abs\/2107.08430"},{"key":"1776_CR17","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y, Hu H, Wei Y, Zhang Z, Lin S, Guo B (2021) Swin transformer: hierarchical vision transformer using shifted windows. In: 2021 IEEE\/CVF international conference on computer vision (ICCV), pp 9992\u201310002","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"1776_CR18","doi-asserted-by":"publisher","DOI":"10.4108\/airo.v1i1.2709","author":"G Xu","year":"2022","unstructured":"Xu G, Khan AS, Moshayedi AJ, Zhang X, Shuxin Y (2022) The object detection, perspective and obstacles in robotic: a review. EAI Endorsed Trans AI Robot. https:\/\/doi.org\/10.4108\/airo.v1i1.2709","journal-title":"EAI Endorsed Trans AI Robot"},{"key":"1776_CR19","unstructured":"Bayar E, Aker C (2024) When to extract ReID features: a selective approach for improved multiple object tracking. ArXiv abs\/2409.06617"},{"key":"1776_CR20","unstructured":"Aharon N, Orfaig R, Bobrovsky B (2022) BoT-SORT: robust associations multi-pedestrian tracking. ArXiv abs\/2206.14651"},{"key":"1776_CR21","doi-asserted-by":"publisher","unstructured":"Shim K, Hwang J, Ko K, Kim C (2024) A confidence-aware matching strategy for generalized multi-object tracking. In: 2024 IEEE international conference on image processing (ICIP), pp 4042\u20134048. https:\/\/doi.org\/10.1109\/ICIP51287.2024.10647729","DOI":"10.1109\/ICIP51287.2024.10647729"},{"key":"1776_CR22","doi-asserted-by":"crossref","unstructured":"Seidenschwarz J, O GB, Elezi I, E LL (2022) Simple cues lead to a strong multi-object tracker. In: 2023 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 13813\u201313823","DOI":"10.1109\/CVPR52729.2023.01327"},{"issue":"5","key":"1776_CR23","doi-asserted-by":"publisher","first-page":"7077","DOI":"10.1007\/s40747-024-01475-3","volume":"10","author":"X Feng","year":"2024","unstructured":"Feng X, Liu Y, Yang H, Jiao X, Liu Z (2024) Self-supervised multi-object tracking based on metric learning. Complex Intell Syst 10(5):7077\u20137088. https:\/\/doi.org\/10.1007\/s40747-024-01475-3","journal-title":"Complex Intell Syst"},{"issue":"4","key":"1776_CR24","doi-asserted-by":"publisher","first-page":"5513","DOI":"10.1007\/s40747-024-01426-y","volume":"10","author":"X Feng","year":"2024","unstructured":"Feng X, Jiao X, Wang S, Zhang Z, Liu Y (2024) SCGTracker: object feature embedding enhancement based on graph attention networks for multi-object tracking. Compl Intell Syst 10(4):5513\u20135527","journal-title":"Compl Intell Syst"},{"key":"1776_CR25","doi-asserted-by":"publisher","unstructured":"Zhang Y, Sun P, Jiang Y, Yu D (2022) ByteTrack: multi-object tracking by\u00a0associating every detection box computer vision\u2013ECCV 2022: 17th European Conference, Aviv, Israel, 2022. Springer Nature Switzerland, p 1\u201321. https:\/\/doi.org\/10.1007\/978-3-031-20047-2_1","DOI":"10.1007\/978-3-031-20047-2_1"},{"key":"1776_CR26","unstructured":"Liu Z, Wang X, Wang C, Liu W, Bai X (2023) SparseTrack: multi-object tracking by performing scene decomposition based on pseudo-depth. ArXiv abs\/2306.05238"},{"key":"1776_CR27","doi-asserted-by":"crossref","unstructured":"Cao J, Weng X, Khirodkar R, Pang J, Kitani K (2022) Observation-Centric SORT: Rethinking SORT for robust multi-object tracking. In: 2023 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), 9686\u20139696","DOI":"10.1109\/CVPR52729.2023.00934"},{"key":"1776_CR28","unstructured":"Hashempoor H, Koikara R, Hwang YD (2024) FeatureSORT: essential features for effective tracking. ArXiv abs\/2407.04249"},{"key":"1776_CR29","doi-asserted-by":"crossref","unstructured":"Peng J, Wang C, Wan F, Wu Y, Wang Y, Tai Y, Wang C, Li J, Huang F, Fu Y (2020) Chained-tracker: chaining paired attentive regression results for end-to-end joint multiple-object detection and tracking. In: European Conference on Computer Vision (ECCV), Cham, 2020. Springer International Publishing, p 145\u2013161","DOI":"10.1007\/978-3-030-58548-8_9"},{"key":"1776_CR30","doi-asserted-by":"crossref","unstructured":"Pang J, Qiu L, Li X, Chen H, Li Q, Darrell T, Yu F (2020) Quasi-dense similarity learning for multiple object tracking. In: 2021 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 164\u2013173","DOI":"10.1109\/CVPR46437.2021.00023"},{"key":"1776_CR31","doi-asserted-by":"publisher","first-page":"105770","DOI":"10.1016\/j.engappai.2022.105770","volume":"119","author":"C Tsai","year":"2023","unstructured":"Tsai C, Shen G, Nisar H (2023) Swin-JDE: joint detection and embedding multi-object tracking in crowded scenes based on swin-transformer. Eng Appl Artif INTEL 119:105770","journal-title":"Eng Appl Artif INTEL"},{"key":"1776_CR32","doi-asserted-by":"publisher","first-page":"12783","DOI":"10.1109\/TPAMI.2022.3213073","volume":"45","author":"T Zhu","year":"2021","unstructured":"Zhu T, Hiller M, Ehsanpour M, Ma R, Drummond T, Rezatofighi H (2021) Looking beyond two frames: end-to-end multi-object tracking using spatial and temporal transformers. IEEE Trans Pattern Anal 45:12783\u201312797","journal-title":"IEEE Trans Pattern Anal"},{"key":"1776_CR33","doi-asserted-by":"publisher","first-page":"102721","DOI":"10.1016\/j.inffus.2024.102721","volume":"115","author":"B Xu","year":"2025","unstructured":"Xu B, Yang G (2025) Interpretability research of deep learning: a literature survey. Inform Fus 115:102721. https:\/\/doi.org\/10.1016\/j.inffus.2024.102721","journal-title":"Inform Fus"},{"key":"1776_CR34","doi-asserted-by":"publisher","first-page":"1508","DOI":"10.1109\/TIP.2024.3364828","volume":"33","author":"Y Gao","year":"2024","unstructured":"Gao Y, Xu H, Li J, Gao X (2024) BPMTrack: multi-object tracking with detection box application pattern mining. IEEE Trans Image Process 33:1508\u20131521","journal-title":"IEEE Trans Image Process"},{"key":"1776_CR35","doi-asserted-by":"publisher","first-page":"105303","DOI":"10.1016\/j.imavis.2024.105303","volume":"152","author":"T Zhao","year":"2024","unstructured":"Zhao T, Yang G, Li Y, Lu M, Sun H (2024) Multi-object tracking using score-driven hierarchical association strategy between predicted tracklets and objects. Image Vis Comput 152:105303. https:\/\/doi.org\/10.1016\/j.imavis.2024.105303","journal-title":"Image Vis Comput"},{"key":"1776_CR36","doi-asserted-by":"crossref","unstructured":"O GB, Leal-Taix'E L (2020) Learning a neural solver for multiple object tracking. In: 2020 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 6246\u20136256","DOI":"10.1109\/CVPR42600.2020.00628"},{"key":"1776_CR37","unstructured":"Hornakova A, Henschel R, Rosenhahn B, Swoboda P. (2020). Lifted disjoint paths with application in multiple object tracking. Paper presented at the Proceedings of Machine Learning Research, 0013\u20137\u20131"},{"key":"1776_CR38","doi-asserted-by":"crossref","unstructured":"Dai P, Weng R, Choi W, Zhang C, He Z, Ding W (2021) Learning a proposal classifier for multiple object tracking. In: 2021 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 2443\u20132452","DOI":"10.1109\/CVPR46437.2021.00247"},{"key":"1776_CR39","doi-asserted-by":"crossref","unstructured":"Du Y, Wan J, Zhao Y, Zhang B, Tong Z, Dong J (2021) GIAOTracker: a comprehensive framework for MCMOT with global information and optimizing strategies in VisDrone 2021. In: 2021 IEEE\/CVF international conference on computer vision workshops (ICCVW), pp 2809\u20132819","DOI":"10.1109\/ICCVW54120.2021.00315"},{"key":"1776_CR40","unstructured":"Milan A, E LL, Reid ID, Roth S, Schindler K (2016) MOT16: a benchmark for multi-object tracking. ArXiv abs\/1603.00831"},{"key":"1776_CR41","unstructured":"Dendorfer P, Rezatofighi H, Milan A, Shi JQ, Cremers D, Reid ID, Roth S, Schindler K, Leal-Taix'E L (2020) MOT20: A benchmark for multi object tracking in crowded scenes. ArXiv abs\/2003.09003"},{"issue":"2","key":"1776_CR42","doi-asserted-by":"publisher","first-page":"548","DOI":"10.1007\/s11263-020-01375-2","volume":"129","author":"J Luiten","year":"2021","unstructured":"Luiten J, Osep A, Dendorfer P, Torr P, Geiger A, Leal-Taix EL, Leibe B (2021) HOTA: a higher order metric for evaluating multi-object tracking. Int J Comput Vis 129(2):548\u2013578. https:\/\/doi.org\/10.1007\/s11263-020-01375-2","journal-title":"Int J Comput Vis"},{"key":"1776_CR43","unstructured":"Shao S, Zhao Z, Li B, Xiao T, Yu G, Zhang X, Sun J (2018) CrowdHuman: a benchmark for detecting human in a crowd. ArXiv abs\/1805.00123"},{"key":"1776_CR44","doi-asserted-by":"crossref","unstructured":"Zhang S, Benenson R, Schiele B (2017) CityPersons: a diverse dataset for pedestrian detection. In: 2017 IEEE conference on computer vision and pattern recognition (CVPR), pp 4457\u20134465","DOI":"10.1109\/CVPR.2017.474"},{"key":"1776_CR45","doi-asserted-by":"publisher","unstructured":"He L, Liao X, Liu W, Liu X, Cheng P, Mei T. (2023). FastReID: a pytorch toolbox for general instance re-identification. Paper presented at the the 31st ACM International Conference on Multimedia, New York, NY, USA. https:\/\/doi.org\/10.1145\/3581783.3613460","DOI":"10.1145\/3581783.3613460"},{"key":"1776_CR46","doi-asserted-by":"publisher","first-page":"7820","DOI":"10.1109\/TPAMI.2022.3225078","volume":"45","author":"Y Xu","year":"2021","unstructured":"Xu Y, Ban Y, Delorme G, Gan C, Rus D, Alameda-Pineda X (2021) TransCenter: transformers with dense representations for multiple-object tracking. IEEE Trans Pattern Anal 45:7820\u20137835","journal-title":"IEEE Trans Pattern Anal"},{"key":"1776_CR47","doi-asserted-by":"publisher","first-page":"6571","DOI":"10.1109\/TCSVT.2023.3263884","volume":"33","author":"M Hu","year":"2023","unstructured":"Hu M, Zhu X, Wang H, Cao S, Liu C, Song Q (2023) STDFormer: spatial-temporal motion transformer for multiple object tracking. IEEE Trans Circ Syst Vid 33:6571\u20136594","journal-title":"IEEE Trans Circ Syst Vid"},{"key":"1776_CR48","doi-asserted-by":"publisher","first-page":"2686","DOI":"10.1109\/TMM.2022.3150169","volume":"25","author":"E Yu","year":"2021","unstructured":"Yu E, Li Z, Han S, Wang H (2021) RelationTrack: relation-aware multiple object tracking with decoupled representation. IEEE Trans Multimedia 25:2686\u20132697","journal-title":"IEEE Trans Multimedia"},{"key":"1776_CR49","doi-asserted-by":"publisher","first-page":"109078","DOI":"10.1016\/j.compeleceng.2024.109078","volume":"114","author":"Y Li","year":"2024","unstructured":"Li Y, Zhao H, Liu Q, Liang X, Xiao X (2024) TPTrack: strengthening tracking-by-detection methods from tracklet processing perspectives. Comput Electr Eng 114:109078. https:\/\/doi.org\/10.1016\/j.compeleceng.2024.109078","journal-title":"Comput Electr Eng"},{"key":"1776_CR50","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.2308.00783","author":"M Yang","year":"2023","unstructured":"Yang M, Han G, Yan B, Zhang W, Qi J, Lu H, Wang D (2023) Hybrid-SORT: weak cues matter for online multi-object tracking. Paper presented at the AAAI Conference on Artificial Intelligence. https:\/\/doi.org\/10.48550\/arXiv.2308.00783","journal-title":"Paper presented at the AAAI Conference on Artificial Intelligence"},{"key":"1776_CR51","doi-asserted-by":"crossref","unstructured":"Sun P, Cao J, Jiang Y, Yuan Z, Bai S, Kitani K, Luo P (2021) DanceTrack: multi-object tracking in uniform appearance and diverse motion. In: 2022 IEEE\/CVF conference on computer vision and pattern recognition (CVPR), pp 20961\u201320970","DOI":"10.1109\/CVPR52688.2022.02032"},{"key":"1776_CR52","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2024.3458464","author":"J Xu","year":"2024","unstructured":"Xu J, Li Y, Yang G, He L, Luo K (2024) Multiscale facial expression recognition based on dynamic global and static local attention. IEEE Trans Affect Comput. https:\/\/doi.org\/10.1109\/TAFFC.2024.3458464","journal-title":"IEEE Trans Affect Comput"},{"issue":"4","key":"1776_CR53","doi-asserted-by":"publisher","first-page":"4955","DOI":"10.1007\/s40747-024-01417-z","volume":"10","author":"G Yang","year":"2024","unstructured":"Yang G, He Z, Su Z, Li Y, Hu B (2024) Keyframe recommendation based on feature intercross and fusion. Complex Intell Syst 10(4):4955\u20134971. https:\/\/doi.org\/10.1007\/s40747-024-01417-z","journal-title":"Complex Intell Syst"},{"issue":"1","key":"1776_CR54","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1049\/cvi2.12231","volume":"18","author":"G Yang","year":"2024","unstructured":"Yang G, Lin J, Su Z, Li Y (2024) Visual privacy behaviour recognition for social robots based on an improved generative adversarial network. IET Comput Vis 18(1):110\u2013123. https:\/\/doi.org\/10.1049\/cvi2.12231","journal-title":"IET Comput Vis"}],"container-title":["Complex &amp; Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-024-01776-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s40747-024-01776-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s40747-024-01776-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T16:31:30Z","timestamp":1738945890000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s40747-024-01776-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,15]]},"references-count":54,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["1776"],"URL":"https:\/\/doi.org\/10.1007\/s40747-024-01776-7","relation":{},"ISSN":["2199-4536","2198-6053"],"issn-type":[{"value":"2199-4536","type":"print"},{"value":"2198-6053","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,15]]},"assertion":[{"value":"3 August 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"145"}}