{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T18:43:21Z","timestamp":1772822601399,"version":"3.50.1"},"reference-count":32,"publisher":"Springer Science and Business Media LLC","issue":"14","license":[{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T00:00:00Z","timestamp":1758499200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100005230","name":"Chongqing  Natural   Science Foundation","doi-asserted-by":"crossref","award":["CSTB2024NSCQ-MSX0687"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0687"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Chongqing  Natural   Science Foundation","doi-asserted-by":"crossref","award":["CSTB2024NSCQ-MSX0687"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0687"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Chongqing  Natural   Science Foundation","doi-asserted-by":"crossref","award":["CSTB2024NSCQ-MSX0687"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0687"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Chongqing  Natural   Science Foundation","doi-asserted-by":"crossref","award":["CSTB2024NSCQ-MSX0687"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0687"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100005230","name":"Chongqing  Natural   Science Foundation","doi-asserted-by":"crossref","award":["CSTB2024NSCQ-MSX0687"],"award-info":[{"award-number":["CSTB2024NSCQ-MSX0687"]}],"id":[{"id":"10.13039\/501100005230","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62472010"],"award-info":[{"award-number":["62472010"]}],"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":["62472010"],"award-info":[{"award-number":["62472010"]}],"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":["62472010"],"award-info":[{"award-number":["62472010"]}],"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":["62472010"],"award-info":[{"award-number":["62472010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s11760-025-04574-x","type":"journal-article","created":{"date-parts":[[2025,9,22]],"date-time":"2025-09-22T12:38:20Z","timestamp":1758544700000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["DSA-YOLO: A lightweight framework for industrial defect detection based on YOLOv11 with two-stage cascaded knowledge distillation"],"prefix":"10.1007","volume":"19","author":[{"given":"Xiaofeng","family":"Lian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"He","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jintao","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,9,22]]},"reference":[{"key":"4574_CR1","doi-asserted-by":"crossref","unstructured":"Chen, P., Liu, S., Zhao, H., Jia, J.: Distilling knowledge via knowledge review. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 5008\u20135017 (2021)","DOI":"10.1109\/CVPR46437.2021.00497"},{"key":"4574_CR2","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der\u00a0Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"4574_CR3","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.jare.2021.03.015","volume":"35","author":"A-A Tulbure","year":"2022","unstructured":"Tulbure, A.-A., Tulbure, A.-A., Dulf, E.-H.: A review on modern defect detection models using dcnns-deep convolutional neural networks. J. Adv. Res. 35, 33\u201348 (2022)","journal-title":"J. Adv. Res."},{"key":"4574_CR4","unstructured":"Devlin, J.: Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)"},{"key":"4574_CR5","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":"4574_CR6","unstructured":"Khanam, R., Hussain, M.: Yolov11: An overview of the key architectural enhancements. arXiv preprint arXiv:2410.17725 (2024)"},{"key":"4574_CR7","unstructured":"Han, S., Mao, H., Dally, W.J.: Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding. In 4th International Conference on Learning Representations, ICLR 2016 (2016)"},{"key":"4574_CR8","unstructured":"Tai, C., Xiao, T., Zhang, Y., Wang, X., et al.: Convolutional neural networks with low-rank regularization. arXiv preprint arXiv:1511.06067 (2015)"},{"key":"4574_CR9","unstructured":"Hinton, G.: Distilling the knowledge in a neural network. In: NIPS Deep Learning and Representation Learning Workshop. (2015)"},{"issue":"4","key":"4574_CR10","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1109\/TPAMI.2017.2699184","volume":"40","author":"L-C Chen","year":"2017","unstructured":"Chen, L.-C., Papandreou, G., Kokkinos, I., Murphy, K., Yuille, A.L.: Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs. IEEE Trans. Pattern Anal. Mach. Intell. 40(4), 834\u2013848 (2017)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4574_CR11","doi-asserted-by":"crossref","unstructured":"Lan, W., Dang, J., Wang, Y., Wang, S.: Pedestrian detection based on yolo network model. In: 2018 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 1547\u20131551 (2018). IEEE","DOI":"10.1109\/ICMA.2018.8484698"},{"key":"4574_CR12","unstructured":"Benjumea, A., Teeti, I., Cuzzolin, F., Bradley, A.: Yolo-z: Improving small object detection in yolov5 for autonomous vehicles. arXiv preprint arXiv:2112.11798 (2021)"},{"issue":"1","key":"4574_CR13","doi-asserted-by":"publisher","first-page":"129","DOI":"10.18201\/ijisae.2022.276","volume":"10","author":"NMAA Dazlee","year":"2022","unstructured":"Dazlee, N.M.A.A., Khalil, S.A., Rahman, S.A., Mutalib, S.: Object detection for autonomous vehicles with sensor-based technology using yolo. International journal of intelligent systems and applications in engineering 10(1), 129\u2013134 (2022)","journal-title":"International journal of intelligent systems and applications in engineering"},{"issue":"1","key":"4574_CR14","first-page":"3844770","volume":"2022","author":"Y Zheng","year":"2022","unstructured":"Zheng, Y., Zhang, H.: Video analysis in sports by lightweight object detection network under the background of sports industry development. Comput. Intell. Neurosci. 2022(1), 3844770 (2022)","journal-title":"Comput. Intell. Neurosci."},{"key":"4574_CR15","doi-asserted-by":"crossref","unstructured":"Ma, H., Celik, T., Li, H.: Fer-yolo: Detection and classification based on facial expressions. In: Image and Graphics: 11th International Conference, ICIG 2021, Haikou, China, August 6\u20138, 2021, Proceedings, Part I 11, pp. 28\u201339 (2021). Springer","DOI":"10.1007\/978-3-030-87355-4_3"},{"key":"4574_CR16","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1016\/j.procs.2018.07.112","volume":"133","author":"S Shinde","year":"2018","unstructured":"Shinde, S., Kothari, A., Gupta, V.: Yolo based human action recognition and localization. Procedia computer science 133, 831\u2013838 (2018)","journal-title":"Procedia computer science"},{"key":"4574_CR17","doi-asserted-by":"crossref","unstructured":"Ashraf, A.H., Imran, M., Qahtani, A.M., Alsufyani, A., Almutiry, O., Mahmood, A., Attique, M., Habib, M.: Weapons detection for security and video surveillance using cnn and yolo-v5s. CMC-Comput. Mater. Contin 70(4), 2761\u20132775 (2022)","DOI":"10.32604\/cmc.2022.018785"},{"key":"4574_CR18","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1016\/j.compag.2019.01.012","volume":"157","author":"Y Tian","year":"2019","unstructured":"Tian, Y., Yang, G., Wang, Z., Wang, H., Li, E., Liang, Z.: Apple detection during different growth stages in orchards using the improved yolo-v3 model. Comput. Electron. Agric. 157, 417\u2013426 (2019)","journal-title":"Comput. Electron. Agric."},{"key":"4574_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2020.105742","volume":"178","author":"D Wu","year":"2020","unstructured":"Wu, D., Lv, S., Jiang, M., Song, H.: Using channel pruning-based yolo v4 deep learning algorithm for the real-time and accurate detection of apple flowers in natural environments. Comput. Electron. Agric. 178, 105742 (2020)","journal-title":"Comput. Electron. Agric."},{"key":"4574_CR20","doi-asserted-by":"crossref","unstructured":"Lippi, M., Bonucci, N., Carpio, R.F., Contarini, M., Speranza, S., Gasparri, A.: A yolo-based pest detection system for precision agriculture. In: 2021 29th Mediterranean Conference on Control and Automation (MED), pp. 342\u2013347 (2021). IEEE","DOI":"10.1109\/MED51440.2021.9480344"},{"key":"4574_CR21","doi-asserted-by":"crossref","unstructured":"Yang, W., Jiachun, Z.: Real-time face detection based on yolo. In: 2018 1st IEEE International Conference on Knowledge Innovation and Invention (ICKII), pp. 221\u2013224 (2018). IEEE","DOI":"10.1109\/ICKII.2018.8569109"},{"key":"4574_CR22","doi-asserted-by":"crossref","unstructured":"Ukhwah, E.N., Yuniarno, E.M., Suprapto, Y.K.: Asphalt pavement pothole detection using deep learning method based on yolo neural network. In: 2019 International Seminar on Intelligent Technology and Its Applications (ISITIA), pp. 35\u201340 (2019). IEEE","DOI":"10.1109\/ISITIA.2019.8937176"},{"key":"4574_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2024.105397","volume":"154","author":"Z Liu","year":"2025","unstructured":"Liu, Z., Chen, Y., Gao, Y.: Rotating-yolo: A novel yolo model for remote sensing rotating object detection. Image Vis. Comput. 154, 105397 (2025)","journal-title":"Image Vis. Comput."},{"key":"4574_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2024.105070","volume":"147","author":"D Chaurasia","year":"2024","unstructured":"Chaurasia, D., Patro, B.: Detection of objects in satellite and aerial imagery using channel and spatially attentive yolo-csl for surveillance. Image Vis. Comput. 147, 105070 (2024)","journal-title":"Image Vis. Comput."},{"key":"4574_CR25","doi-asserted-by":"crossref","unstructured":"Bucilu\u01ce, C., Caruana, R., Niculescu-Mizil, A.: Model compression. In: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 535\u2013541 (2006)","DOI":"10.1145\/1150402.1150464"},{"key":"4574_CR26","doi-asserted-by":"crossref","unstructured":"Yu, R., Li, A., Morariu, V.I., Davis, L.S.: Visual relationship detection with internal and external linguistic knowledge distillation. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1974\u20131982 (2017)","DOI":"10.1109\/ICCV.2017.121"},{"key":"4574_CR27","unstructured":"Chen, G., Choi, W., Yu, X., Han, T., Chandraker, M.: Learning efficient object detection models with knowledge distillation. Adv. Neural Inf. Process Syst. 30 (2017)"},{"key":"4574_CR28","unstructured":"Romero, A., Ballas, N., Kahou, S.E., Chassang, A., Gatta, C., Bengio, Y.: Fitnets: Hints for thin deep nets. arXiv preprint arXiv:1412.6550 (2014)"},{"key":"4574_CR29","unstructured":"Zagoruyko, S., Komodakis, N.: Paying more attention to attention: Improving the performance of convolutional neural networks via attention transfer. arXiv preprint arXiv:1612.03928 (2016)"},{"issue":"5","key":"4574_CR30","doi-asserted-by":"publisher","first-page":"2030","DOI":"10.1109\/TNNLS.2020.2995884","volume":"32","author":"N Passalis","year":"2020","unstructured":"Passalis, N., Tzelepi, M., Tefas, A.: Probabilistic knowledge transfer for lightweight deep representation learning. IEEE Trans. Neural Netw. Learn. Syst. 32(5), 2030\u20132039 (2020)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"4574_CR31","doi-asserted-by":"crossref","unstructured":"Yim, J., Joo, D., Bae, J., Kim, J.: A gift from knowledge distillation: Fast optimization, network minimization and transfer learning. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4133\u20134141 (2017)","DOI":"10.1109\/CVPR.2017.754"},{"key":"4574_CR32","doi-asserted-by":"crossref","unstructured":"Park, W., Kim, D., Lu, Y., Cho, M.: Relational knowledge distillation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 3967\u20133976 (2019)","DOI":"10.1109\/CVPR.2019.00409"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04574-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04574-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04574-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T18:56:46Z","timestamp":1761418606000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04574-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,22]]},"references-count":32,"journal-issue":{"issue":"14","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["4574"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04574-x","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"value":"1863-1703","type":"print"},{"value":"1863-1711","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,22]]},"assertion":[{"value":"4 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 July 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 September 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no conflicts of interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflicts of Interest"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"1188"}}