{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T13:47:54Z","timestamp":1769003274696,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:00:00Z","timestamp":1733443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2023M732022"],"award-info":[{"award-number":["2023M732022"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100016087","name":"Qufu Normal University","doi-asserted-by":"publisher","award":["167\/602801"],"award-info":[{"award-number":["167\/602801"]}],"id":[{"id":"10.13039\/100016087","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1007\/s10489-024-05984-z","type":"journal-article","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T08:25:08Z","timestamp":1733473508000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Searching a lightweight network architecture for thermal infrared pedestrian tracking"],"prefix":"10.1007","volume":"55","author":[{"given":"Wen-Jia","family":"Tang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2230-3937","authenticated-orcid":false,"given":"Peng","family":"Gao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ru-Yue","family":"Yuan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,12,6]]},"reference":[{"key":"5984_CR1","doi-asserted-by":"crossref","unstructured":"Yuan D, Shu X, Liu Q (2022) Recent advances on thermal infrared target tracking: a survey. In: Asian conference on artificial intelligence technology, pp 1\u20136","DOI":"10.1109\/ACAIT56212.2022.10137986"},{"key":"5984_CR2","doi-asserted-by":"crossref","unstructured":"Yuan D, Zhang H, Shu X, Liu Q, Chang Q, He Z, Shi G (2023) Thermal infrared target tracking: a comprehensive review. IEEE Trans Instrum Meas","DOI":"10.1109\/TIM.2023.3338701"},{"key":"5984_CR3","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2012) Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097\u20131105"},{"key":"5984_CR4","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: IEEE Conference on computer vision and pattern recognition, pp 770\u2013778","DOI":"10.1109\/CVPR.2016.90"},{"key":"5984_CR5","doi-asserted-by":"publisher","first-page":"1269","DOI":"10.1109\/TMM.2022.3140929","volume":"25","author":"Q Liu","year":"2022","unstructured":"Liu Q, Yuan D, Fan N, Gao P, Li X, He Z (2022) Learning dual-level deep representation for thermal infrared tracking. IEEE Trans Multimedia 25:1269\u20131281","journal-title":"IEEE Trans Multimedia"},{"key":"5984_CR6","doi-asserted-by":"crossref","unstructured":"Gao P, Ma Y, Song K, Li C, Wang F, Xiao L (2018) Large margin structured convolution operator for thermal infrared object tracking. In: IEEE International conference on pattern recognition, pp 2380\u20132385","DOI":"10.1109\/ICPR.2018.8545716"},{"issue":"3","key":"5984_CR7","first-page":"1224","volume":"70","author":"D Yuan","year":"2022","unstructured":"Yuan D, Shu X, Liu Q, He Z (2022) Aligned spatial-temporal memory network for thermal infrared target tracking. IEEE Trans Circuits Syst II Express Briefs 70(3):1224\u20131228","journal-title":"IEEE Trans Circuits Syst II Express Briefs"},{"key":"5984_CR8","doi-asserted-by":"crossref","unstructured":"Wang W, Zhang X, Cui H, Yin H, Zhang Y (2023) Fp-darts: fast parallel differentiable neural architecture search for image classification. Pattern Recognit 136(109193)","DOI":"10.1016\/j.patcog.2022.109193"},{"key":"5984_CR9","doi-asserted-by":"publisher","first-page":"6893","DOI":"10.1109\/TIP.2022.3216771","volume":"31","author":"T Liang","year":"2022","unstructured":"Liang T, Chu X, Liu Y, Wang Y, Tang Z, Chu W, Chen J, Ling H (2022) Cbnet: a composite backbone network architecture for object detection. IEEE Trans Image Process 31:6893\u20136906","journal-title":"IEEE Trans Image Process"},{"issue":"17","key":"5984_CR10","doi-asserted-by":"publisher","first-page":"3623","DOI":"10.3390\/electronics12173623","volume":"12","author":"P Gao","year":"2023","unstructured":"Gao P, Liu X, Sang H-C, Wang Y, Wang F (2023) Efficient and lightweight visual tracking with differentiable neural architecture search. Electronics 12(17):3623","journal-title":"Electronics"},{"key":"5984_CR11","doi-asserted-by":"crossref","unstructured":"Wang W, Zhuo T, Zhang X, Sun M, Yin H, Xing Y, Zhang Y (2023) Automatic network architecture search for rgb-d semantic segmentation. In: ACM International conference on multimedia, pp 3777\u20133786","DOI":"10.1145\/3581783.3612288"},{"key":"5984_CR12","doi-asserted-by":"crossref","unstructured":"Zoph B, Vasudevan V, Shlens J, Le QV (2018) Learning transferable architectures for scalable image recognition. In: IEEE Conference on computer vision and pattern recognition, pp 8697\u20138710","DOI":"10.1109\/CVPR.2018.00907"},{"key":"5984_CR13","doi-asserted-by":"crossref","unstructured":"Real E, Aggarwal A, Huang Y, Le QV (2019) Regularized evolution for image classifier architecture search. In: AAAI Conference on artificial intelligence, vol\u00a033, pp 4780\u20134789","DOI":"10.1609\/aaai.v33i01.33014780"},{"key":"5984_CR14","doi-asserted-by":"crossref","unstructured":"Bhat G, Danelljan M, Gool LV, Timofte R (2019) Learning discriminative model prediction for tracking. In: International Conference on Computer Vision (ICCV). IEEE, pp 6182\u20136191","DOI":"10.1109\/ICCV.2019.00628"},{"key":"5984_CR15","unstructured":"Xu Y, Xie L, Zhang X, Chen X, Qi G-J, Tian Q, Xiong H (2019) Pc-darts: partial channel connections for memory-efficient architecture search. In: International conference on learning representations"},{"key":"5984_CR16","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.patrec.2017.10.026","volume":"100","author":"X Yu","year":"2017","unstructured":"Yu X, Yu Q, Shang Y, Zhang H (2017) Dense structural learning for infrared object tracking at 200+ frames per second. Pattern Recogn Lett 100:152\u2013159","journal-title":"Pattern Recogn Lett"},{"key":"5984_CR17","doi-asserted-by":"crossref","unstructured":"Gundogdu E, Koc A, Solmaz B, Hammoud RI, Aydin Alatan A (2016) Evaluation of feature channels for correlation-filter-based visual object tracking in infrared spectrum. In: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp 24\u201332","DOI":"10.1109\/CVPRW.2016.43"},{"key":"5984_CR18","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1016\/j.knosys.2017.07.032","volume":"134","author":"Q Liu","year":"2017","unstructured":"Liu Q, Lu X, He Z, Zhang C, Chen W-S (2017) Deep convolutional neural networks for thermal infrared object tracking. Knowl-Based Syst 134:189\u2013198","journal-title":"Knowl-Based Syst"},{"key":"5984_CR19","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.knosys.2018.12.011","volume":"166","author":"X Li","year":"2019","unstructured":"Li X, Liu Q, Fan N, He Z, Wang H (2019) Hierarchical spatial-aware siamese network for thermal infrared object tracking. Knowl-Based Syst 166:71\u201381","journal-title":"Knowl-Based Syst"},{"key":"5984_CR20","doi-asserted-by":"publisher","first-page":"2114","DOI":"10.1109\/TMM.2020.3008028","volume":"23","author":"Q Liu","year":"2020","unstructured":"Liu Q, Li X, He Z, Fan N, Yuan D, Wang H (2020) Learning deep multi-level similarity for thermal infrared object tracking. IEEE Trans Multimedia 23:2114\u20132126","journal-title":"IEEE Trans Multimedia"},{"key":"5984_CR21","unstructured":"Zoph B, Le QV Neural architecture search with reinforcement learning. arXiv:1611.01578"},{"key":"5984_CR22","doi-asserted-by":"crossref","unstructured":"Cai H, Chen T, Zhang W, Yu Y, Wang J (2018) Efficient architecture search by network transformation. In: Proceedings of the AAAI conference on artificial intelligence, vol\u00a032","DOI":"10.1609\/aaai.v32i1.11709"},{"key":"5984_CR23","unstructured":"Pham H, Guan M, Zoph B, Le Q, Dean J (2018) Efficient neural architecture search via parameters sharing. In: International conference on machine learning. PMLR, pp 4095\u20134104"},{"key":"5984_CR24","unstructured":"Liu H, Simonyan K, Yang Y(2018) Darts: differentiable architecture search. In: International conference on learning representations"},{"key":"5984_CR25","doi-asserted-by":"crossref","unstructured":"Liu Q, Li X, Yuan D, Yang C, Chang X, He Z (2023) Lsotb-tir: a large-scale high-diversity thermal infrared single object tracking benchmark. IEEE Trans Neural Netw Learn Syst","DOI":"10.1109\/TNNLS.2023.3236895"},{"issue":"3","key":"5984_CR26","doi-asserted-by":"publisher","first-page":"666","DOI":"10.1109\/TMM.2019.2932615","volume":"22","author":"Q Liu","year":"2019","unstructured":"Liu Q, He Z, Li X, Zheng Y (2019) Ptb-tir: a thermal infrared pedestrian tracking benchmark. IEEE Trans Multimedia 22(3):666\u2013675","journal-title":"IEEE Trans Multimedia"},{"key":"5984_CR27","unstructured":"Kingma DP, Ba J (2014) Adam: a method for stochastic optimization. arXiv:1412.6980"},{"key":"5984_CR28","unstructured":"Loshchilov I, Hutter F (2016) Sgdr: stochastic gradient descent with warm restarts. arXiv:1608.03983"},{"key":"5984_CR29","doi-asserted-by":"publisher","first-page":"111665","DOI":"10.1016\/j.knosys.2024.111665","volume":"293","author":"P Gao","year":"2024","unstructured":"Gao P, Li S-M, Gao F, Wang F, Yuan R-Y, Fujita H (2024) In defense and revival of bayesian filtering for thermal infrared object tracking. Knowl-Based Syst 293:111665","journal-title":"Knowl-Based Syst"},{"key":"5984_CR30","doi-asserted-by":"crossref","unstructured":"Danelljan M, Bhat G, Khan SF, Felsberg M (2017) Eco: Efficient convolution operators for tracking. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 6931\u20136939","DOI":"10.1109\/CVPR.2017.733"},{"issue":"4","key":"5984_CR31","doi-asserted-by":"publisher","first-page":"1837","DOI":"10.1109\/TIP.2018.2879249","volume":"28","author":"L Zhang","year":"2018","unstructured":"Zhang L, Gonzalez-Garcia A, Van De Weijer J, Danelljan M, Khan FS (2018) Synthetic data generation for end-to-end thermal infrared tracking. IEEE Trans Image Process 28(4):1837\u20131850","journal-title":"IEEE Trans Image Process"},{"key":"5984_CR32","doi-asserted-by":"crossref","unstructured":"Nam H, Han B (2016) Learning multi-domain convolutional neural networks for visual tracking. In: IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, pp 4293\u20134302","DOI":"10.1109\/CVPR.2016.465"},{"key":"5984_CR33","doi-asserted-by":"crossref","unstructured":"Bertinetto L, Valmadre J, Henriques J, Vedaldi A, Torr PHS (2016) Fully-convolutional siamese networks for object tracking. In: European conference on computer vision (ECCV). Springer-Verlag, pp 850\u2013865","DOI":"10.1007\/978-3-319-48881-3_56"},{"key":"5984_CR34","doi-asserted-by":"crossref","unstructured":"Dong X, Shen J (2018) Triplet loss in siamese network for object tracking. In: European Conference on Computer Vision (ECCV), pp 459\u2013474","DOI":"10.1007\/978-3-030-01261-8_28"},{"key":"5984_CR35","doi-asserted-by":"crossref","unstructured":"Li X, Ma C, Wu B, He Z, Yang M-H (2019) Target-aware deep tracking. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 1369\u20131378","DOI":"10.1109\/CVPR.2019.00146"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05984-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-05984-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-05984-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T15:03:52Z","timestamp":1737385432000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-05984-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,6]]},"references-count":35,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,1]]}},"alternative-id":["5984"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-05984-z","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,6]]},"assertion":[{"value":"30 September 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 December 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest\/Competing Interests"}}],"article-number":"91"}}