{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T10:42:52Z","timestamp":1789468972006,"version":"build-2803163510"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T00:00:00Z","timestamp":1787529600000},"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":["Multimedia Systems"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1007\/s00530-026-02616-z","type":"journal-article","created":{"date-parts":[[2026,8,24]],"date-time":"2026-08-24T10:03:45Z","timestamp":1787565825000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["MBHS-DETR: a lightweight collaborative network for bearing surface defect detection"],"prefix":"10.1007","volume":"32","author":[{"given":"Shoubin","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiwei","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guili","family":"Peng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kun","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tong","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenxue","family":"Liang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shaojie","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,24]]},"reference":[{"key":"2616_CR1","doi-asserted-by":"publisher","first-page":"29857","DOI":"10.1109\/ACCESS.2020.2972859","volume":"8","author":"S Zhang","year":"2020","unstructured":"Zhang, S., Zhang, S., Wang, B., et al.: Deep learning algorithms for bearing fault diagnostics\u2014A comprehensive review. IEEE access. 8, 29857\u201329881 (2020)","journal-title":"IEEE access."},{"issue":"2","key":"2616_CR2","doi-asserted-by":"publisher","first-page":"485","DOI":"10.1016\/j.ymssp.2010.07.017","volume":"25","author":"RB Randall","year":"2011","unstructured":"Randall, R.B., Antoni, J.: Rolling element bearing diagnostics\u2014A tutorial. Mech. Syst. Signal Process. 25(2), 485\u2013520 (2011)","journal-title":"Mech. Syst. Signal Process."},{"issue":"4","key":"2616_CR3","doi-asserted-by":"publisher","first-page":"21","DOI":"10.3390\/machines5040021","volume":"5","author":"W Caesarendra","year":"2017","unstructured":"Caesarendra, W., Tjahjowidodo, T.: A review of feature extraction methods in vibration-based condition monitoring and its application for degradation trend estimation of low-speed slew bearing. Machines. 5(4), 21 (2017)","journal-title":"Machines"},{"issue":"3","key":"2616_CR4","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1007\/s10845-019-01476-x","volume":"31","author":"D Tabernik","year":"2020","unstructured":"Tabernik, D., \u0160ela, S., Skvar\u010d, J., et al.: Segmentation-based deep-learning approach for surface-defect detection. J. Intell. Manuf. 31(3), 759\u2013776 (2020)","journal-title":"J. Intell. Manuf."},{"key":"2616_CR5","doi-asserted-by":"crossref","unstructured":"Xie, X.: A review of recent advances in surface defect detection using texture analysis techniques. ELCVIA: Electron. Lett. Comput. Vis. image Anal. 7(3),1\u201322. (2008)","DOI":"10.5565\/rev\/elcvia.268"},{"issue":"1","key":"2616_CR6","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1186\/1687-5281-2014-50","volume":"2014","author":"N Neogi","year":"2014","unstructured":"Neogi, N., Mohanta, D.K., Dutta, P.K.: Review of vision-based steel surface inspection systems. EURASIP J. Image Video Process. 2014(1), 50 (2014)","journal-title":"EURASIP J. Image Video Process."},{"key":"2616_CR7","doi-asserted-by":"crossref","unstructured":"Girshick, R.: Fast r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. : 1440\u20131448. (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"2616_CR8","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., et al.: Feature pyramid networks for object detection[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. : 2117\u20132125. (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"2616_CR9","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., et al.: You only look once: Unified, real-time object detection[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. : 779\u2013788. (2016)","DOI":"10.1109\/CVPR.2016.91"},{"issue":"5","key":"2616_CR10","doi-asserted-by":"publisher","first-page":"6672","DOI":"10.1016\/j.ceramint.2021.11.217","volume":"48","author":"Y Dongling","year":"2022","unstructured":"Dongling, Y., Xiaohui, Z., Jianzhen, Z., et al.: An enhancement algorithm based on adaptive updating template with Gaussian model for Si3N4 ceramic bearing roller surface defects detection. Ceram. Int. 48(5), 6672\u20136680 (2022)","journal-title":"Ceram. Int."},{"issue":"4","key":"2616_CR11","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1364\/JOSAA.449088","volume":"39","author":"D Liao","year":"2022","unstructured":"Liao, D., Yin, M., Luo, H., et al.: Machine vision system based on a coupled image segmentation algorithm for surface-defect detection of a Si3N4 bearing roller. J. Opt. Soc. Am. A. 39(4), 571\u2013579 (2022)","journal-title":"J. Opt. Soc. Am. A"},{"issue":"4","key":"2616_CR12","doi-asserted-by":"publisher","first-page":"1825","DOI":"10.3390\/app11041825","volume":"11","author":"M Lu","year":"2021","unstructured":"Lu, M., Chen, C.L.: Detection and classification of bearing surface defects based on machine vision. Appl. Sci. 11(4), 1825 (2021)","journal-title":"Appl. Sci."},{"issue":"13","key":"2616_CR13","doi-asserted-by":"publisher","first-page":"6569","DOI":"10.3390\/app12136569","volume":"12","author":"H Gao","year":"2022","unstructured":"Gao, H., Zhang, Y., Lv, W., et al.: A deep convolutional generative adversarial networks-based method for defect detection in small sample industrial parts images. Appl. Sci. 12(13), 6569 (2022)","journal-title":"Appl. Sci."},{"issue":"4","key":"2616_CR14","doi-asserted-by":"publisher","first-page":"1493","DOI":"10.1109\/TIM.2019.2915404","volume":"69","author":"Y He","year":"2019","unstructured":"He, Y., Song, K., Meng, Q., et al.: An end-to-end steel surface defect detection approach via fusing multiple hierarchical features. IEEE Trans. Instrum. Meas. 69(4), 1493\u20131504 (2019)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"9","key":"2616_CR15","doi-asserted-by":"publisher","first-page":"4825","DOI":"10.3390\/app15094825","volume":"15","author":"Z Jiang","year":"2025","unstructured":"Jiang, Z., Fu, J., Zeng, T., et al.: Defect R-CNN: A novel high-precision method for CT image defect detection. Appl. Sci. 15(9), 4825 (2025)","journal-title":"Appl. Sci."},{"issue":"4","key":"2616_CR16","doi-asserted-by":"publisher","first-page":"041002","DOI":"10.1115\/1.4063860","volume":"24","author":"Y Wang","year":"2024","unstructured":"Wang, Y., Wang, X., Hao, R., et al.: Metal surface defect detection method based on improved cascade r-cnn. J. Comput. Inf. Sci. Eng. 24(4), 041002 (2024)","journal-title":"J. Comput. Inf. Sci. Eng."},{"issue":"10","key":"2616_CR17","doi-asserted-by":"publisher","first-page":"e0310007","DOI":"10.1371\/journal.pone.0310007","volume":"19","author":"K Li","year":"2024","unstructured":"Li, K., Jiao, P., Ding, J., et al.: Bearing defect detection based on the improved YOLOv5 algorithm. PloS one. 19(10), e0310007 (2024)","journal-title":"PloS one"},{"key":"2616_CR18","doi-asserted-by":"publisher","first-page":"1722962","DOI":"10.3389\/fphy.2025.1722962","volume":"13","author":"H Jin","year":"2025","unstructured":"Jin, H., Li, M., Huang, C., et al.: LSA-YOLO: a bearing surface defect detection method based on low-order response aggregation and progressive attention. Front. Phys. 13, 1722962 (2025)","journal-title":"Front. Phys."},{"issue":"1","key":"2616_CR19","doi-asserted-by":"publisher","first-page":"e0292082","DOI":"10.1371\/journal.pone.0292082","volume":"19","author":"Q Wang","year":"2024","unstructured":"Wang, Q., Dong, H., Huang, H.: Swin-Transformer-YOLOv5 for lightweight hot-rolled steel strips surface defect detection algorithm. Plos one. 19(1), e0292082 (2024)","journal-title":"Plos one"},{"issue":"5","key":"2616_CR20","doi-asserted-by":"publisher","first-page":"930","DOI":"10.3390\/pr12050930","volume":"12","author":"M Liu","year":"2024","unstructured":"Liu, M., Zhang, M., Chen, X., et al.: YOLOv8-LMG: an improved bearing defect detection algorithm based on YOLOv8. Processes. 12(5), 930 (2024)","journal-title":"Processes"},{"key":"2616_CR21","doi-asserted-by":"publisher","first-page":"107984","DOI":"10.52202\/079017-3429","volume":"37","author":"A Wang","year":"2024","unstructured":"Wang, A., Chen, H., Liu, L., et al.: Yolov10: Real-time end-to-end object detection. Adv. Neural. Inf. Process. Syst. 37, 107984\u2013108011 (2024)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"2616_CR22","unstructured":"Zhu, X., Su, W., Lu, L., et al.: Deformable detr: Deformable transformers for end-to-end object detection. arXiv preprint arXiv:2010.04159 (2020)."},{"key":"2616_CR23","doi-asserted-by":"publisher","first-page":"103318","DOI":"10.1016\/j.aei.2025.103318","volume":"65","author":"G Liu","year":"2025","unstructured":"Liu, G., Yang, D., Ye, J., et al.: A real-time welding defect detection framework based on RT-DETR deep neural network. Adv. Eng. Inform. 65, 103318 (2025)","journal-title":"Adv. Eng. Inform."},{"issue":"11","key":"2616_CR24","doi-asserted-by":"publisher","first-page":"952","DOI":"10.1007\/s11760-025-04548-z","volume":"19","author":"L Qu","year":"2025","unstructured":"Qu, L., Wen, F., Huang, H., et al.: CEH-RTDETR: A lightweight and efficient industrial component defect detection model based on improved RT-DETR: L. Qu et al. Signal. Image Video Process. 19(11), 952 (2025)","journal-title":"Signal. Image Video Process."},{"key":"2616_CR25","doi-asserted-by":"publisher","first-page":"113956","DOI":"10.1016\/j.optlastec.2025.113956","volume":"192","author":"P Shi","year":"2025","unstructured":"Shi, P., Jiang, H., Li, X., et al.: Surface defect detection of magnetic tile based on RT-DETR improved algorithm. Opt. Laser Technol. 192, 113956 (2025)","journal-title":"Opt. Laser Technol."},{"key":"2616_CR26","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Lv, W., Xu, S., et al.: Detrs beat yolos on real-time object detection[C]\/\/Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. : 16965\u201316974. (2024)","DOI":"10.1109\/CVPR52733.2024.01605"},{"issue":"5","key":"2616_CR27","doi-asserted-by":"publisher","first-page":"1357","DOI":"10.3390\/pr11051357","volume":"11","author":"L Wang","year":"2023","unstructured":"Wang, L., Liu, X., Ma, J., et al.: Real-time steel surface defect detection with improved multi-scale YOLO-v5. Processes. 11(5), 1357 (2023)","journal-title":"Processes"},{"key":"2616_CR28","doi-asserted-by":"crossref","unstructured":"Varghese, R., Sambath, M.: Yolov8: A novel object detection algorithm with enhanced performance and robustness[C]\/\/2024 International conference on advances in data engineering and intelligent computing systems (ADICS). IEEE, : 1\u20136. (2024)","DOI":"10.1109\/ADICS58448.2024.10533619"},{"key":"2616_CR29","doi-asserted-by":"crossref","unstructured":"Wang, J., Meng, R., Zhang, Y., et al.: Airport runway FOD detection model based on improved YOLOv10m[C]\/\/Journal of Physics: Conference Series. IOP Publishing, 2879(1): 012045. (2024)","DOI":"10.1088\/1742-6596\/2879\/1\/012045"},{"key":"2616_CR30","unstructured":"Khanam, R., Hussain, M.: Yolov11: An overview of the key architectural enhancements (2024) . arXiv preprint arXiv:2410.17725, (2024)"},{"key":"2616_CR31","doi-asserted-by":"crossref","unstructured":"Tobias Schlagenhauf and Magnus Landwehr: Data Brief. 39, 107643 (2021). Industrial machine tool component surface defect dataset","DOI":"10.1016\/j.dib.2021.107643"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-026-02616-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-026-02616-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-026-02616-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T09:15:43Z","timestamp":1789463743000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-026-02616-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,24]]},"references-count":31,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["2616"],"URL":"https:\/\/doi.org\/10.1007\/s00530-026-02616-z","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,24]]},"assertion":[{"value":"1 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 August 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 August 2026","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","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"533"}}