{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T06:22:37Z","timestamp":1778048557584,"version":"3.51.4"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T00:00:00Z","timestamp":1716336000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T00:00:00Z","timestamp":1716336000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Science and Technology Research Program of Chongqing Municipal Education Commission","award":["KJZD-M202300502"],"award-info":[{"award-number":["KJZD-M202300502"]}]},{"name":"Science and Technology Research Program of Chongqing Municipal Education Commission","award":["KJQN202200537"],"award-info":[{"award-number":["KJQN202200537"]}]},{"DOI":"10.13039\/501100005230","name":"Natural Science Foundation of Chongqing","doi-asserted-by":"crossref","award":["CSTB2022NSCQ-MSX1200"],"award-info":[{"award-number":["CSTB2022NSCQ-MSX1200"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Chongqing Normal University Ph.D. Start-up Fund","award":["21XLB035"],"award-info":[{"award-number":["21XLB035"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s00371-024-03434-y","type":"journal-article","created":{"date-parts":[[2024,5,22]],"date-time":"2024-05-22T11:01:51Z","timestamp":1716375711000},"page":"1467-1484","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["YOLO-SSP: an object detection model based on pyramid spatial attention and improved downsampling strategy for remote sensing images"],"prefix":"10.1007","volume":"41","author":[{"given":"Yongli","family":"Liu","sequence":"first","affiliation":[]},{"given":"Degang","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Tingting","family":"Song","sequence":"additional","affiliation":[]},{"given":"Yichen","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Xin","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,5,22]]},"reference":[{"key":"3434_CR1","doi-asserted-by":"publisher","first-page":"11058","DOI":"10.1109\/JSTARS.2021.3123080","volume":"14","author":"P Qin","year":"2021","unstructured":"Qin, P., Cai, Y., Liu, J., Fan, P., Sun, M.: Multilayer feature extraction network for military ship detection from high-resolution optical remote sensing images. IEEE J. Sel. Top. Appl. Earth. Obs. Remote Sens. 14, 11058\u201311069 (2021)","journal-title":"IEEE J. Sel. Top. Appl. Earth. Obs. Remote Sens."},{"issue":"3","key":"3434_CR2","doi-asserted-by":"publisher","first-page":"592","DOI":"10.3390\/rs14030592","volume":"14","author":"R Reedha","year":"2022","unstructured":"Reedha, R., Dericquebourg, E., Canals, R., Hafiane, A.: Transformer neural network for weed and crop classification of high resolution UAV images. Remote Sens. 14(3), 592 (2022)","journal-title":"Remote Sens."},{"issue":"2","key":"3434_CR3","doi-asserted-by":"publisher","first-page":"418","DOI":"10.3390\/rs15020418","volume":"15","author":"V Gagliardi","year":"2023","unstructured":"Gagliardi, V., Tosti, F., Bianchini Ciampoli, L., Battagliere, M.L., D\u2019Amato, L., Alani, A.M., Benedetto, A.: Satellite remote sensing and non-destructive testing methods for transport infrastructure monitoring: advances, challenges and perspectives. Remote Sens. 15(2), 418 (2023)","journal-title":"Remote Sens."},{"key":"3434_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2020.111706","volume":"242","author":"F Chen","year":"2020","unstructured":"Chen, F., Chen, X., Voorde, T., Roberts, D., Jiang, H., Xu, W.: Open water detection in urban environments using high spatial resolution remote sensing imagery. Remote Sens. Environ. 242, 111706 (2020)","journal-title":"Remote Sens. Environ."},{"issue":"4","key":"3434_CR5","doi-asserted-by":"publisher","first-page":"1995","DOI":"10.1007\/s10845-021-01878-w","volume":"34","author":"SA Singh","year":"2023","unstructured":"Singh, S.A., Desai, K.: Automated surface defect detection framework using machine vision and convolutional neural networks. J. Intell. Manuf. 34(4), 1995\u20132011 (2023)","journal-title":"J. Intell. Manuf."},{"issue":"4","key":"3434_CR6","doi-asserted-by":"publisher","first-page":"1560","DOI":"10.1109\/TITS.2019.2909275","volume":"21","author":"J Leng","year":"2019","unstructured":"Leng, J., Liu, Y., Du, D., Zhang, T., Quan, P.: Robust obstacle detection and recognition for driver assistance systems. IEEE Trans. Intell. Transp. Syst. 21(4), 1560\u20131571 (2019)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"1","key":"3434_CR7","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1109\/TII.2021.3085669","volume":"18","author":"J Li","year":"2022","unstructured":"Li, J., Chen, J., Sheng, B., Li, P., Yang, P., Feng, D.D., Qi, J.: Automatic detection and classification system of domestic waste via multimodel cascaded convolutional neural network. IEEE Trans. Ind. Inf. 18(1), 163\u2013173 (2022)","journal-title":"IEEE Trans. Ind. Inf."},{"key":"3434_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109512","volume":"253","author":"Z Han","year":"2022","unstructured":"Han, Z., Jian, M., Wang, G.-G.: Convunext: an efficient convolution neural network for medical image segmentation. Knowl. Based Syst. 253, 109512 (2022)","journal-title":"Knowl. Based Syst."},{"issue":"6","key":"3434_CR9","doi-asserted-by":"publisher","first-page":"1440","DOI":"10.1007\/s11263-022-01583-y","volume":"130","author":"J Pan","year":"2022","unstructured":"Pan, J., Sun, D., Zhang, J., Tang, J., Yang, J., Tai, Y.-W., Yang, M.-H.: Dual convolutional neural networks for low-level vision. Int. J. Comput. Vis. 130(6), 1440\u20131458 (2022)","journal-title":"Int. J. Comput. Vis."},{"key":"3434_CR10","doi-asserted-by":"publisher","first-page":"3765","DOI":"10.1109\/TMM.2023.3315558","volume":"26","author":"J Leng","year":"2024","unstructured":"Leng, J., Liu, Y., Gao, X., Wang, Z.: Crnet: context-guided reasoning network for detecting hard objects. IEEE Trans. Multimed. 26, 3765\u20133777 (2024)","journal-title":"IEEE Trans. Multimed."},{"issue":"3","key":"3434_CR11","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/JPROC.2023.3238524","volume":"111","author":"Z Zou","year":"2023","unstructured":"Zou, Z., Chen, K., Shi, Z., Guo, Y., Ye, J.: Object detection in 20 years: a survey. Proc. IEEE 111(3), 257\u2013276 (2023)","journal-title":"Proc. IEEE"},{"key":"3434_CR12","doi-asserted-by":"crossref","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 580\u2013587 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"issue":"1","key":"3434_CR13","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1109\/TPAMI.2015.2437384","volume":"38","author":"R Girshick","year":"2015","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Region-based convolutional networks for accurate object detection and segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 38(1), 142\u2013158 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"9","key":"3434_CR14","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"K He","year":"2015","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1904\u20131916 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"3434_CR15","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"3434_CR16","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: Towards real-time object detection with region proposal networks. Adv. Neural Inf. Process. Syst. 28, 91\u201399 (2015)"},{"key":"3434_CR17","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., Girshick, R.: Mask r-cnn. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"key":"3434_CR18","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., Farhadi, A.: You only look once: Unified, real-time object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 779\u2013788 (2016)","DOI":"10.1109\/CVPR.2016.91"},{"key":"3434_CR19","doi-asserted-by":"crossref","unstructured":"Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., Berg, A.C.: Ssd: single shot multibox detector. In: Proceedings of the European Conference on Computer Vision, pp. 21\u201337 (2016)","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"3434_CR20","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Goyal, P., Girshick, R., He, K., Doll\u00e1r, P.: Focal loss for dense object detection. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2980\u20132988 (2017)","DOI":"10.1109\/ICCV.2017.324"},{"key":"3434_CR21","doi-asserted-by":"crossref","unstructured":"Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., Zagoruyko, S.: End-to-end object detection with transformers. In: Proceedings of the European Conference on Computer Vision, pp. 213\u2013229 (2020)","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"3434_CR22","unstructured":"Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, \u0141., Polosukhin, I.: Attention is all you need. Adv. Neural Inf. Process. Syst. 30, 5998\u20136008 (2017)"},{"issue":"17","key":"3434_CR23","doi-asserted-by":"publisher","first-page":"4383","DOI":"10.3390\/rs14174383","volume":"14","author":"L Jian","year":"2022","unstructured":"Jian, L., Pu, Z., Zhu, L., Yao, T., Liang, X.: Ss R-CNN: self-supervised learning improving mask R-CNN for ship detection in remote sensing images. Remote Sens. 14(17), 4383 (2022)","journal-title":"Remote Sens."},{"key":"3434_CR24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2020.3034752","volume":"60","author":"G Cheng","year":"2021","unstructured":"Cheng, G., Yan, B., Shi, P., Li, K., Yao, X., Guo, L., Han, J.: Prototype-CNN for few-shot object detection in remote sensing images. IEEE Trans. Geosci. Remote Sens. 60, 1\u201310 (2021)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"3","key":"3434_CR25","doi-asserted-by":"publisher","first-page":"1320","DOI":"10.1109\/TCSVT.2022.3210207","volume":"33","author":"J Leng","year":"2022","unstructured":"Leng, J., Mo, M., Zhou, Y., Gao, C., Li, W., Gao, X.: Pareto refocusing for drone-view object detection. IEEE Trans. Circuits Syst. Video Technol. 33(3), 1320\u20131334 (2022)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"issue":"18","key":"3434_CR26","doi-asserted-by":"publisher","first-page":"4459","DOI":"10.3390\/rs15184459","volume":"15","author":"X Liu","year":"2023","unstructured":"Liu, X., Gong, W., Shang, L., Li, X., Gong, Z.: Remote sensing image target detection and recognition based on yolov5. Remote Sens. 15(18), 4459 (2023)","journal-title":"Remote Sens."},{"issue":"15","key":"3434_CR27","doi-asserted-by":"publisher","first-page":"3863","DOI":"10.3390\/rs15153863","volume":"15","author":"T Xie","year":"2023","unstructured":"Xie, T., Han, W., Xu, S.: Yolo-rs: a more accurate and faster object detection method for remote sensing images. Remote Sens. 15(15), 3863 (2023)","journal-title":"Remote Sens."},{"issue":"14","key":"3434_CR28","doi-asserted-by":"publisher","first-page":"6414","DOI":"10.3390\/s23146414","volume":"23","author":"Z Li","year":"2023","unstructured":"Li, Z., Yuan, J., Li, G., Wang, H., Li, X., Li, D., Wang, X.: Rsi-yolo: object detection method for remote sensing images based on improved yolo. Sensors 23(14), 6414 (2023)","journal-title":"Sensors"},{"key":"3434_CR29","first-page":"1","volume":"62","author":"J Li","year":"2024","unstructured":"Li, J., Tian, P., Song, R., Xu, H., Li, Y., Du, Q.: Pcvit: a pyramid convolutional vision transformer detector for object detection in remote-sensing imagery. IEEE Trans. Geosci. Remote Sens. 62, 1\u201315 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3434_CR30","first-page":"1","volume":"62","author":"Y Cao","year":"2024","unstructured":"Cao, Y., Guo, L., Xiong, F., Kuang, L., Han, X.: Physical-simulation-based dynamic template matching method for remote sensing small object detection. IEEE Trans. Geosci. Remote Sens. 62, 1\u201314 (2024)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3434_CR31","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"3434_CR32","doi-asserted-by":"crossref","unstructured":"Wang, Q., Wu, B., Zhu, P., Li, P., Zuo, W., Hu, Q.: Eca-net: Efficient channel attention for deep convolutional neural networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 11534\u201311542 (2020)","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"3434_CR33","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.-Y., Kweon, I.S.: Cbam: convolutional block attention module. In: Proceedings of the European Conference on Computer Vision, pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"3434_CR34","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J.: Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 13713\u201313722 (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"3434_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2023.104855","volume":"140","author":"T Song","year":"2023","unstructured":"Song, T., Zhang, X., Yang, D., Ye, Y., Liu, C., Zhou, J., Song, Y.: Lightweight detection network based on receptive-field feature enhancement convolution and three dimensions attention for images captured by UAVS. Image Vis. Comput. 140, 104855 (2023)","journal-title":"Image Vis. Comput."},{"issue":"4","key":"3434_CR36","doi-asserted-by":"publisher","first-page":"2300","DOI":"10.1109\/TCYB.2020.3004636","volume":"52","author":"L Cui","year":"2020","unstructured":"Cui, L., Lv, P., Jiang, X., Gao, Z., Zhou, B., Zhang, L., Shao, L., Xu, M.: Context-aware block net for small object detection. IEEE Trans. Cybern. 52(4), 2300\u20132313 (2020)","journal-title":"IEEE Trans. Cybern."},{"key":"3434_CR37","doi-asserted-by":"crossref","unstructured":"Sunkara, R., Luo, T.: No more strided convolutions or pooling: A new cnn building block for low-resolution images and small objects. In: Joint European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 443\u2013459 (2022)","DOI":"10.1007\/978-3-031-26409-2_27"},{"key":"3434_CR38","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1016\/j.isprsjprs.2019.11.023","volume":"159","author":"K Li","year":"2020","unstructured":"Li, K., Wan, G., Cheng, G., Meng, L., Han, J.: Object detection in optical remote sensing images: a survey and a new benchmark. ISPRS J. Photogramm. Remote. Sens. 159, 296\u2013307 (2020)","journal-title":"ISPRS J. Photogramm. Remote. Sens."},{"issue":"8","key":"3434_CR39","doi-asserted-by":"publisher","first-page":"5535","DOI":"10.1109\/TGRS.2019.2900302","volume":"57","author":"Y Zhang","year":"2019","unstructured":"Zhang, Y., Yuan, Y., Feng, Y., Lu, X.: Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection. IEEE Trans. Geosci. Remote Sens. 57(8), 5535\u20135548 (2019)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"3434_CR40","doi-asserted-by":"publisher","first-page":"3032","DOI":"10.1109\/JSTARS.2020.3000317","volume":"13","author":"M Haroon","year":"2020","unstructured":"Haroon, M., Shahzad, M., Fraz, M.M.: Multisized object detection using spaceborne optical imagery. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 13, 3032\u20133046 (2020)","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"3434_CR41","unstructured":"Redmon, J., Farhadi, A.: Yolov3: an incremental improvement. arXiv preprint arXiv:1804.02767 (2018)"},{"key":"3434_CR42","unstructured":"Glenn, J.: Yolov5 release v6.0. Github:ultralytics\/yolov5 (2022)"},{"key":"3434_CR43","doi-asserted-by":"crossref","unstructured":"Wang, C.-Y., Bochkovskiy, A., Liao, H.-Y.M.: Yolov7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7464\u20137475 (2023)","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"3434_CR44","unstructured":"Glenn, J.: Ultralytics yolov8. Github:ultralytics\/yolov8 (2023)"},{"key":"3434_CR45","doi-asserted-by":"crossref","unstructured":"Hu, M., Li, Z., Yu, J., Wan, X., Tan, H., Lin, Z.: Efficient-lightweight yolo: improving small object detection in yolo for aerial images. Sensors 23(14), 6423 (2023)","DOI":"10.3390\/s23146423"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03434-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-024-03434-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-024-03434-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,12]],"date-time":"2025-02-12T14:53:44Z","timestamp":1739372024000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-024-03434-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,22]]},"references-count":45,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["3434"],"URL":"https:\/\/doi.org\/10.1007\/s00371-024-03434-y","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,5,22]]},"assertion":[{"value":"23 April 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 May 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":"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"}}]}}