{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T15:58:11Z","timestamp":1768233491554,"version":"3.49.0"},"publisher-location":"Singapore","reference-count":26,"publisher":"Springer Nature Singapore","isbn-type":[{"value":"9789819557547","type":"print"},{"value":"9789819557554","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-981-95-5755-4_15","type":"book-chapter","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T12:30:19Z","timestamp":1768221019000},"page":"217-231","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Rethinking Lightweight Multi-scale Detection of Foreign Objects on Transmission Lines"],"prefix":"10.1007","author":[{"given":"Hui","family":"Wang","sequence":"first","affiliation":[]},{"given":"Zhonglin","family":"Wu","sequence":"additional","affiliation":[]},{"given":"Feng","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Chunhua","family":"Xie","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,13]]},"reference":[{"key":"15_CR1","doi-asserted-by":"crossref","unstructured":"Chen, W., Li, Y., Li, C.: A visual detection method for foreign objects in power lines based on mask r-cnn. Int. J. Ambient Comput. Intell. (IJACI) 34\u201347 (2020)","DOI":"10.4018\/IJACI.2020010102"},{"key":"15_CR2","doi-asserted-by":"crossref","unstructured":"Chen, X., Zhang, Z., Zhang, G., Yu, Z., Qin, H., Zhang, R., Song, Y., Liu, Q.: Faster r-cnn for multi-class foreign objects detection of transmission lines. In: IEEE 6th International Electrical and Energy Conference (CIEEC), pp. 2233\u20132238. IEEE (2023)","DOI":"10.1109\/CIEEC58067.2023.10167107"},{"key":"15_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2024.107917","volume":"170","author":"Y Chen","year":"2024","unstructured":"Chen, Y., Zhang, C., Chen, B., Huang, Y., Sun, Y., Wang, C., Fu, X., Dai, Y., Qin, F., Peng, Y., Gao, Y.: Accurate leukocyte detection based on deformable-detr and multi-level feature fusion for aiding diagnosis of blood diseases. Comput. Biol. Med. 170, 107917 (2024)","journal-title":"Comput. Biol. Med."},{"issue":"1","key":"15_CR4","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1038\/s41597-024-02918-9","volume":"11","author":"Z Chen","year":"2024","unstructured":"Chen, Z., Yang, J., Feng, Z., Zhu, H.: Railfod23: a dataset for foreign object detection on railroad transmission lines. Sci. Data 11(1), 72 (2024)","journal-title":"Sci. Data"},{"key":"15_CR5","doi-asserted-by":"crossref","unstructured":"Feng, C., Zhong, Y., Gao, Y., Scott, M.R., Huang, W.: Tood: task-aligned one-stage object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), pp. 3490\u20133499 (2021)","DOI":"10.1109\/ICCV48922.2021.00349"},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Hu, J., Shen, L., Sun, G.: Squeeze-and-excitation networks. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 7132\u20137141 (2018)","DOI":"10.1109\/CVPR.2018.00745"},{"key":"15_CR7","doi-asserted-by":"publisher","first-page":"6083","DOI":"10.1016\/j.egyr.2024.05.061","volume":"11","author":"S Li","year":"2024","unstructured":"Li, S., Wang, Z., Lv, Y., Liu, X.: Improved yolov5s-based algorithm for foreign object intrusion detection on overhead transmission lines. Energy Rep. 11, 6083\u20136093 (2024)","journal-title":"Energy Rep."},{"key":"15_CR8","unstructured":"Paddle, B.: Southern power grid transmission line foreign object dataset (spgfod). Dataset (2024). https:\/\/aistudio.baidu.com\/datasetdetail\/325064\/0"},{"key":"15_CR9","doi-asserted-by":"crossref","unstructured":"Rahman, M.M., Munir, M., Marculescu, R.: Emcad: efficient multi-scale convolutional attention decoding for medical image segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 11769\u201311779 (2024)","DOI":"10.1109\/CVPR52733.2024.01118"},{"issue":"6","key":"15_CR10","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2015","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster r-cnn: towards real-time object detection with region proposal networks. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 39(6), 1137\u20131149 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"15_CR11","doi-asserted-by":"crossref","unstructured":"Shi, D.: Transnext: robust foveal visual perception for vision transformers. arXiv preprint arXiv:2311.17132 (2023)","DOI":"10.1109\/CVPR52733.2024.01683"},{"key":"15_CR12","doi-asserted-by":"crossref","unstructured":"Tan, M., Pang, R., Le, Q.V.: Efficientdet: scalable and efficient object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 10781\u201310790 (2020)","DOI":"10.1109\/CVPR42600.2020.01079"},{"issue":"5","key":"15_CR13","doi-asserted-by":"publisher","first-page":"3003","DOI":"10.1007\/s00371-023-03004-8","volume":"40","author":"C Tang","year":"2024","unstructured":"Tang, C., Dong, H., Huang, Y., Han, T., Fang, M., Fu, J.: Foreign object detection for transmission lines based on swin transformer v2 and yolox. Vis. Comput. 40(5), 3003\u20133021 (2024)","journal-title":"Vis. Comput."},{"key":"15_CR14","unstructured":"Tian, Y., Ye, Q., Doermann, D.: Yolov12: attention-centric real-time object detectors. arXiv preprint arXiv:2502.12524 (2025)"},{"issue":"6","key":"15_CR15","first-page":"1922","volume":"43","author":"Z Tian","year":"2020","unstructured":"Tian, Z., Shen, C., Chen, H., He, T.: Fcos: a simple and strong anchor-free object detector. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 43(6), 1922\u20131933 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"15_CR16","doi-asserted-by":"crossref","unstructured":"Wang, A., Chen, H., Liu, L., Chen, K., Lin, Z., Han, J., Ding, G.: Yolov10: real-time end-to-end object detection. In: Advances in Neural Information Processing Systems (NeurIPS), pp. 107984\u2013108011 (2024)","DOI":"10.52202\/079017-3429"},{"key":"15_CR17","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Liao, H.Y.M., Yeh, I.H., Wu, Y.H., Chen, P.Y., Hsieh, J.W.: Cspnet: a new backbone that can enhance learning capability of cnn. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 390\u2013391 (2020)","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"15_CR18","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Yeh, I.H., Liao, H.Y.M.: Yolov9: Learning what you want to learn using programmable gradient information. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 1\u201321 (2024)","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"15_CR19","unstructured":"Williams, T., Li, R.: Wavelet pooling for convolutional neural networks. In: International Conference on Learning Representations (ICLR) (2018)"},{"key":"15_CR20","doi-asserted-by":"publisher","first-page":"1169","DOI":"10.1109\/TIP.2020.3042065","volume":"30","author":"T Wu","year":"2020","unstructured":"Wu, T., Tang, S., Zhang, R., Cao, J., Zhang, Y.: Cgnet: a light-weight context guided network for semantic segmentation. IEEE Trans. Image Process. 30, 1169\u20131179 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"15_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109819","volume":"143","author":"G Xu","year":"2023","unstructured":"Xu, G., Liao, W., Zhang, X., Li, C., He, X., Wu, X.: Haar wavelet downsampling: a simple but effective downsampling module for semantic segmentation. Pattern Recogn. 143, 109819 (2023)","journal-title":"Pattern Recogn."},{"key":"15_CR22","unstructured":"Xu, X., Jiang, Y., Chen, W., Huang, Y., Zhang, Y., Sun, X.: Damo-yolo: a report on real-time object detection design. arXiv preprint arXiv:2211.15444 (2022)"},{"key":"15_CR23","doi-asserted-by":"crossref","unstructured":"Yang, Z., Guan, Q., Zhao, K., Yang, J., Xu, X., Long, H., Tang, Y.: Multi-branch auxiliary fusion yolo with re-parameterization heterogeneous convolutional for accurate object detection. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp. 492\u2013505 (2024)","DOI":"10.1007\/978-981-97-8858-3_34"},{"issue":"2","key":"15_CR24","doi-asserted-by":"publisher","first-page":"896","DOI":"10.1109\/TPAMI.2023.3329173","volume":"46","author":"W Yu","year":"2024","unstructured":"Yu, W., Si, C., Zhou, P., Luo, M., Zhou, Y., Feng, J., Yan, S., Wang, X.: Metaformer baselines for vision. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI) 46(2), 896\u2013912 (2024)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI)"},{"key":"15_CR25","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Lv, W., Xu, S., Wei, J., Wang, G., Dang, Q., Liu, Y., Chen, J.: Detrs beat yolos on real-time object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16965\u201316974 (2024)","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"15_CR26","doi-asserted-by":"crossref","unstructured":"Zhu, X., Hu, H., Lin, S., Dai, J.: Deformable convnets v2: More deformable, better results. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). pp. 9308\u20139316 (2019)","DOI":"10.1109\/CVPR.2019.00953"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition and Computer Vision"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-95-5755-4_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T12:30:42Z","timestamp":1768221042000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-95-5755-4_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9789819557547","9789819557554"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-981-95-5755-4_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"13 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PRCV","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Chinese Conference on Pattern Recognition and Computer Vision  (PRCV)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Shanghai","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 October 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ccprcv2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2025.prcv.cn\/index.asp","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}