{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,11]],"date-time":"2025-06-11T07:32:49Z","timestamp":1749627169086,"version":"3.37.3"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,7,27]],"date-time":"2024-07-27T00:00:00Z","timestamp":1722038400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2024,7,27]],"date-time":"2024-07-27T00:00:00Z","timestamp":1722038400000},"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":["U1803261"],"award-info":[{"award-number":["U1803261"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Sci Rep"],"DOI":"10.1038\/s41598-024-68129-9","type":"journal-article","created":{"date-parts":[[2024,7,27]],"date-time":"2024-07-27T03:28:34Z","timestamp":1722050914000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Research on the perception method of tiny objects in low-light and wide-field video"],"prefix":"10.1038","volume":"14","author":[{"given":"Zhaodong","family":"Xie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenhong","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Baoqiang","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,27]]},"reference":[{"key":"68129_CR1","doi-asserted-by":"crossref","unstructured":"Zeng, B. -W. and K. T. U. Low-light image enhancement algorithm based on lime with pre-processing and post-processing. In 2020 International Conference on Wavelet Analysis and Pattern Recognition, pp. 96\u2013101 (2020).","DOI":"10.1109\/ICWAPR51924.2020.9494618"},{"key":"68129_CR2","doi-asserted-by":"publisher","first-page":"5862","DOI":"10.1109\/TIP.2020.2984098","volume":"29","author":"X Ren","year":"2020","unstructured":"Ren, X., Yang, W., Cheng, W.-H. & Liu, J. LR3M: Robust low-light enhancement via low-rank regularized retinex model. IEEE Trans. Image Process. 29, 5862\u20135876 (2020).","journal-title":"IEEE Trans. Image Process."},{"key":"68129_CR3","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zhang, J. and Gu, X. Kindling the darkness: A practical low-light image enhancer. In Proc. of the 27th ACM International Conference on Multimedia. Association for Computing Machinery, 1632\u20131640 (2019).","DOI":"10.1145\/3343031.3350926"},{"issue":"12","key":"68129_CR4","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.1109\/LGRS.2016.2611001","volume":"13","author":"F Gao","year":"2016","unstructured":"Gao, F., Dong, J., Li, B. & Xu, Q. Automatic change detection in synthetic aperture radar images based on PCANet. IEEE Geosci. Remote Sens. Lett. 13(12), 1792\u20131796 (2016).","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"3","key":"68129_CR5","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1109\/TNNLS.2016.2636227","volume":"29","author":"J Liu","year":"2018","unstructured":"Liu, J., Gong, M., Qin, K. & Zhang, P. A deep convolutional coupling network for change detection based on heterogeneous optical and radar images. IEEE Trans. Neural Netw. Learn. Syst. 29(3), 545\u2013559 (2018).","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"11","key":"68129_CR6","doi-asserted-by":"publisher","first-page":"4517","DOI":"10.1109\/JSTARS.2019.2953128","volume":"12","author":"Y Gao","year":"2019","unstructured":"Gao, Y., Gao, F., Dong, J. & Wang, S. Change detection from synthetic aperture radar images based on channel weighting-based deep cascade network. IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens. 12(11), 4517\u20134529 (2019).","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"68129_CR7","doi-asserted-by":"publisher","first-page":"43970","DOI":"10.1109\/ACCESS.2019.2908282","volume":"7","author":"L Liu","year":"2019","unstructured":"Liu, L., Jia, Z., Yang, J. & Kasabov, N. K. SAR image change detection based on mathematical morphology and the k-means clustering algorithm. IEEE Access 7, 43970\u201343978 (2019).","journal-title":"IEEE Access"},{"issue":"2","key":"68129_CR8","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1109\/LGRS.2017.2786344","volume":"15","author":"P Planin\u0161i\u010d","year":"2018","unstructured":"Planin\u0161i\u010d, P. & Gleich, D. Temporal change detection in SAR images using log cumulants and stacked autoencoder. IEEE Geosci. Remote Sens. Lett. 15(2), 297\u2013301 (2018).","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"68129_CR9","doi-asserted-by":"crossref","unstructured":"Rouag, F. E., Terki, N. and Touil, D. E. Improving the correlation filter-based tracking using low-illumination enhancement method. In 2020 1st International Conference on Communications, Control Systems and Signal Processing, pp. 207\u2013210 (2020).","DOI":"10.1109\/CCSSP49278.2020.9151629"},{"key":"68129_CR10","first-page":"380","volume":"2016","author":"SA Priyanka","year":"2016","unstructured":"Priyanka, S. A., Tung, H.-J. & Wang, Y. K. Contrast enhancement of night images. Int. Conf. Mach. Learn. Cybern. 2016, 380\u2013385 (2016).","journal-title":"Int. Conf. Mach. Learn. Cybern."},{"issue":"2","key":"68129_CR11","doi-asserted-by":"publisher","first-page":"982","DOI":"10.1109\/TIP.2016.2639450","volume":"26","author":"X Guo","year":"2017","unstructured":"Guo, X., Li, Y. & Ling, H. LIME: Low-light image enhancement via illumination map estimation. IEEE Trans. Image Process. 26(2), 982\u2013993 (2017).","journal-title":"IEEE Trans. Image Process."},{"key":"68129_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2022.3162892","author":"B Li","year":"2022","unstructured":"Li, B. et al. All-day object tracking for unmanned aerial vehicle. IEEE Trans. Mobile Comput. https:\/\/doi.org\/10.1109\/TMC.2022.3162892 (2022).","journal-title":"IEEE Trans. Mobile Comput."},{"key":"68129_CR13","first-page":"153","volume":"2013","author":"H Ahn","year":"2013","unstructured":"Ahn, H., Keum, B., Kim, D. & Lee, H. S. Adaptive local tone mapping based on retinex for high dynamic range images. IEEE Int. Conf. Consum. Electron. 2013, 153\u2013156 (2013).","journal-title":"IEEE Int. Conf. Consum. Electron."},{"key":"68129_CR14","first-page":"3079","volume":"2021","author":"J Ye","year":"2021","unstructured":"Ye, J., Fu, C., Zheng, G., Cao, Z. & Li, B. DarkLighter: Light up the darkness for UAV tracking. IEEE Int. Conf. Intell. Robots Syst. 2021, 3079\u20133085 (2021).","journal-title":"IEEE Int. Conf. Intell. Robots Syst."},{"key":"68129_CR15","first-page":"1144","volume":"2017","author":"HK Galoogahi","year":"2017","unstructured":"Galoogahi, H. K., Fagg, A. & Lucey, S. Learning background-aware correlation filters for visual tracking. IEEE Int. Conf. Comput. Vis. 2017, 1144\u20131152 (2017).","journal-title":"IEEE Int. Conf. Comput. Vis."},{"key":"68129_CR16","first-page":"4904","volume":"2018","author":"F Li","year":"2018","unstructured":"Li, F., Tian, C., Zuo, W., Zhang, L. & Yang, M.-H. Learning spatial-temporal regularized correlation filters for visual tracking. IEEE Conf. Comput. Vis. Pattern Recognit. 2018, 4904\u20134913 (2018).","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"issue":"1","key":"68129_CR17","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1561\/2200000016","volume":"3","author":"S Boyd","year":"2011","unstructured":"Boyd, S. et al. Distributed optimization and statistical learning via the alternating direction method of multipliers. Found. Trends Mach. Learn. 3(1), 1\u2013122 (2011).","journal-title":"Found. Trends Mach. Learn."},{"key":"68129_CR18","first-page":"11920","volume":"2020","author":"Y Li","year":"2020","unstructured":"Li, Y., Fu, C., Ding, F., Huang, Z. & Lu, G. AutoTrack: Towards high-performance visual tracking for UAV with automatic spatio-temporal regularization. IEEE\/CVF Conf. Comput. Vis. Pattern Recognit. 2020, 11920\u201311929 (2020).","journal-title":"IEEE\/CVF Conf. Comput. Vis. Pattern Recognit."},{"key":"68129_CR19","first-page":"6931","volume":"2017","author":"M Danelljan","year":"2017","unstructured":"Danelljan, M., Bhat, G., Khan, F. S. & Felsberg, M. ECO: Efficient convolution operators for tracking. IEEE Conf. Comput. Vis. Pattern Recognit. 2017, 6931\u20136939 (2017).","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"68129_CR20","first-page":"1401","volume":"2016","author":"L Bertinetto","year":"2016","unstructured":"Bertinetto, L., Valmadre, J., Golodetz, S., Miksik, O. & Torr, P. H. S. Staple: Complementary learners for real-time tracking. IEEE Conf. Comput. Vis. Pattern Recognit. 2016, 1401\u20131409 (2016).","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"68129_CR21","first-page":"472","volume-title":"European Conference on Computer Vision","author":"M Danelljan","year":"2016","unstructured":"Danelljan, M. et al. Beyond correlation filters: Learning continuous convolution operators for visual tracking. In European Conference on Computer Vision (eds Danelljan, M., Robinson, A., Shahbaz Khan, F. et al.) 472\u2013488 (Springer, 2016)."},{"key":"68129_CR22","first-page":"4665","volume":"2019","author":"K Dai","year":"2019","unstructured":"Dai, K., Wang, D., Lu, H., Sun, C. & Li, J. Visual tracking via adaptive spatially-regularized correlation filters. IEEE Conf. Comput. Vis. Pattern Recognit. 2019, 4665\u20134674 (2019).","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"68129_CR23","first-page":"3074","volume":"2015","author":"C Ma","year":"2015","unstructured":"Ma, C., Huang, J.-B., Yang, X. & Yang, M.-H. Hierarchical convolutional features for visual tracking. IEEE Int. Conf. Comput. Vis 2015, 3074\u20133082 (2015).","journal-title":"IEEE Int. Conf. Comput. Vis"},{"key":"68129_CR24","first-page":"4321","volume":"2016","author":"J Choi","year":"2016","unstructured":"Choi, J., Chang, H. J., Jeong, J., Demiris, Y. & Choi, J. Y. Visual tracking using attention-modulated disintegration and integration. IEEE Conf. Comput. Vis. Pattern Recognit. 2016, 4321\u20134330 (2016).","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"68129_CR25","first-page":"4844","volume":"2018","author":"N Wang","year":"2018","unstructured":"Wang, N. et al. Multi-cue correlation filters for robust visual tracking. IEEE Conf. Comput. Vis. Pattern Recognit. 2018, 4844\u20134853 (2018).","journal-title":"IEEE Conf. Comput. Vis. Pattern Recognit."},{"key":"68129_CR26","first-page":"2891","volume":"2019","author":"Z Huang","year":"2019","unstructured":"Huang, Z., Fu, C., Li, Y., Lin, F. & Lu, P. Learning aberrance repressed correlation filters for real-time UAV tracking. IEEE Int. Conf. Comput. Vis. 2019, 2891\u20132900 (2019).","journal-title":"IEEE Int. Conf. Comput. Vis."},{"key":"68129_CR27","first-page":"7949","volume":"2019","author":"T Xu","year":"2019","unstructured":"Xu, T., Feng, Z.-H., Wu, X.-J. & Kittler, J. Joint group feature selection and discriminative filter learning for robust visual object tracking. IEEE Int. Conf. Comput. Vis. 2019, 7949\u20137959 (2019).","journal-title":"IEEE Int. Conf. Comput. Vis."}],"container-title":["Scientific Reports"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-68129-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-68129-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-68129-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,27]],"date-time":"2024-07-27T03:30:19Z","timestamp":1722051019000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41598-024-68129-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,27]]},"references-count":27,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,12]]}},"alternative-id":["68129"],"URL":"https:\/\/doi.org\/10.1038\/s41598-024-68129-9","relation":{},"ISSN":["2045-2322"],"issn-type":[{"type":"electronic","value":"2045-2322"}],"subject":[],"published":{"date-parts":[[2024,7,27]]},"assertion":[{"value":"6 June 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 July 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 July 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"17249"}}