{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T08:09:56Z","timestamp":1778486996619,"version":"3.51.4"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/100014103","name":"Key Research and Development Program of Shandong Province","doi-asserted-by":"crossref","award":["2023CXGC010203"],"award-info":[{"award-number":["2023CXGC010203"]}],"id":[{"id":"10.13039\/100014103","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1007\/s11554-026-01885-1","type":"journal-article","created":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T02:54:29Z","timestamp":1776048869000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["YOLOv11-LCCAP2: deployment-oriented P2 head and contrast-aware attention for metal surface micro-defect detection"],"prefix":"10.1007","volume":"23","author":[{"given":"Mingzhi","family":"Chen","sequence":"first","affiliation":[]},{"given":"Ping","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Yuan","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Guodong","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,4,13]]},"reference":[{"key":"1885_CR1","doi-asserted-by":"crossref","unstructured":"Chen, L.C., Zhu, Y., Papandreou, G., Schroff, F., Adam, H.: Encoder\u2013decoder with atrous separable convolution for semantic image segmentation. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 801\u2013818 (2018)","DOI":"10.1007\/978-3-030-01234-2_49"},{"key":"1885_CR2","doi-asserted-by":"crossref","unstructured":"Chen, Y., Li, W., Sakaridis, C., Dai, D., Van\u00a0Gool, L.: Domain adaptive faster r-cnn for object detection in the wild. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3339\u20133348 (2018)","DOI":"10.1109\/CVPR.2018.00352"},{"key":"1885_CR3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2020.2991573","volume":"70","author":"X Cheng","year":"2020","unstructured":"Cheng, X., Yu, J.: Retinanet with difference channel attention and adaptively spatial feature fusion for steel surface defect detection. IEEE Trans. Instrum. Meas. 70, 1\u201311 (2020)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"2","key":"1885_CR4","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/s11263-009-0275-4","volume":"88","author":"M Everingham","year":"2010","unstructured":"Everingham, M., Van Gool, L., Williams, C.K., Winn, J., Zisserman, A.: The pascal visual object classes (voc) challenge. Int. J. Comput. Vis. 88(2), 303\u2013338 (2010)","journal-title":"Int. J. Comput. Vis."},{"key":"1885_CR5","unstructured":"Ge, Z., Liu, S., Wang, F., Li, Z., Sun, J.: Yolox: exceeding yolo series in 2021. arXiv preprint arXiv:2107.08430 (2021)"},{"key":"1885_CR6","unstructured":"Hafeez, H., Garratt, M., Plested, J., Iyer, S., Sowmya, A.: Yolo11-4k: an efficient architecture for real-time small object detection in 4k panoramic images. arXiv preprint arXiv:2512.16493 (2025)"},{"key":"1885_CR7","doi-asserted-by":"crossref","unstructured":"Han, K., Wang, Y., Tian, Q., Guo, J., Xu, C., Xu, C.: Ghostnet: More features from cheap operations. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 1580\u20131589 (2020)","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"1885_CR8","doi-asserted-by":"crossref","unstructured":"Hou, Q., Zhou, D., Feng, J.: Coordinate attention for efficient mobile network design. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 13713\u201313722 (2021)","DOI":"10.1109\/CVPR46437.2021.01350"},{"key":"1885_CR9","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":"1885_CR10","doi-asserted-by":"crossref","unstructured":"Huang, J., Rathod, V., Sun, C., Zhu, M., Korattikara, A., Fathi, A., Fischer, I., Wojna, Z., Song, Y., Guadarrama, S., et\u00a0al.: Speed\/accuracy trade-offs for modern convolutional object detectors. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7310\u20137311 (2017)","DOI":"10.1109\/CVPR.2017.351"},{"key":"1885_CR11","unstructured":"Jocher, G., Chaurasia, A., Qiu, J.: Ultralytics yolov8. https:\/\/github.com\/ultralytics\/ultralytics (2023)"},{"key":"1885_CR12","unstructured":"Jocher, G., Qiu, J.: Ultralytics yolo11. https:\/\/github.com\/ultralytics\/ultralytics (2024)"},{"key":"1885_CR13","doi-asserted-by":"publisher","unstructured":"Jocher, G., et\u00a0al.: ultralytics\/yolov5: v6.2. https:\/\/doi.org\/10.5281\/zenodo.7002879. https:\/\/github.com\/ultralytics\/yolov5 (2022)","DOI":"10.5281\/zenodo.7002879"},{"key":"1885_CR14","doi-asserted-by":"crossref","unstructured":"Khan, I.U., Aslam, N., Aboulnour, M., Bashamakh, A., Alghool, F., Alsuwayan, N., Alturaif, R., Gull, H., Iqbal, S.Z., Hussain, T.: Deep learning-based surface defect detection in steel products using convolutional neural networks. Math. Model. Eng. Probl. 11(11) (2024)","DOI":"10.18280\/mmep.111113"},{"key":"1885_CR15","doi-asserted-by":"crossref","unstructured":"Li, M., Wei, L., Zheng, B.: Steel surface defect detection based on improved yolov7. In: 2024 4th International Conference on Computer, Control and Robotics (ICCCR), pp. 51\u201355. IEEE (2024)","DOI":"10.1109\/ICCCR61138.2024.10585576"},{"key":"1885_CR16","doi-asserted-by":"crossref","unstructured":"Li, Y., Chen, Y., Wang, N., Zhang, Z.: Scale-aware trident networks for object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 6054\u20136063 (2019)","DOI":"10.1109\/ICCV.2019.00615"},{"key":"1885_CR17","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., He, K., Hariharan, B., Belongie, S.: Feature pyramid networks for object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2117\u20132125 (2017)","DOI":"10.1109\/CVPR.2017.106"},{"key":"1885_CR18","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":"1885_CR19","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., Zitnick, C.L.: Microsoft coco: common objects in context. In: European Conference on Computer Vision, pp. 740\u2013755. Springer (2014)","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"1885_CR20","doi-asserted-by":"crossref","unstructured":"Liu, S., Qi, L., Qin, H., Shi, J., Jia, J.: Path aggregation network for instance segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8759\u20138768 (2018)","DOI":"10.1109\/CVPR.2018.00913"},{"key":"1885_CR21","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: European Conference on Computer Vision, pp. 21\u201337. Springer (2016)","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"1885_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114602","volume":"172","author":"Y Liu","year":"2021","unstructured":"Liu, Y., Sun, P., Wergeles, N., Shang, Y.: A survey and performance evaluation of deep learning methods for small object detection. Expert Syst. Appl. 172, 114602 (2021)","journal-title":"Expert Syst. Appl."},{"issue":"6","key":"1885_CR23","doi-asserted-by":"publisher","first-page":"1562","DOI":"10.3390\/s20061562","volume":"20","author":"X Lv","year":"2020","unstructured":"Lv, X., Duan, F., Jiang, J.J., Fu, X., Gan, L.: Deep metallic surface defect detection: the new benchmark and detection network. Sensors 20(6), 1562 (2020)","journal-title":"Sensors"},{"key":"1885_CR24","doi-asserted-by":"crossref","unstructured":"Ma, N., Zhang, X., Zheng, H.T., Sun, J.: Shufflenet v2: practical guidelines for efficient cnn architecture design. In: Proceedings of the European Conference on Computer Vision (ECCV), pp. 116\u2013131 (2018)","DOI":"10.1007\/978-3-030-01264-9_8"},{"key":"1885_CR25","doi-asserted-by":"publisher","first-page":"43370","DOI":"10.1109\/ACCESS.2023.3271748","volume":"11","author":"M Prunella","year":"2023","unstructured":"Prunella, M., Scardigno, R.M., Buongiorno, D., Brunetti, A., Longo, N., Carli, R., Dotoli, M., Bevilacqua, V.: Deep learning for automatic vision-based recognition of industrial surface defects: a survey. IEEE Access 11, 43370\u201343423 (2023)","journal-title":"IEEE Access"},{"key":"1885_CR26","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":"1885_CR27","unstructured":"Redmon, J., Farhadi, A.: Yolov3: an incremental improvement. arXiv preprint arXiv:1804.02767 (2018)"},{"key":"1885_CR28","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 (2015)"},{"key":"1885_CR29","doi-asserted-by":"crossref","unstructured":"Sohan, M., Sai\u00a0Ram, T., Rami\u00a0Reddy, C.V.: A review on yolov8 and its advancements. In: International Conference on Data Intelligence and Cognitive Informatics, pp. 529\u2013545. Springer (2024)","DOI":"10.1007\/978-981-99-7962-2_39"},{"key":"1885_CR30","doi-asserted-by":"publisher","first-page":"858","DOI":"10.1016\/j.apsusc.2013.09.002","volume":"285","author":"K Song","year":"2013","unstructured":"Song, K., Yan, Y.: A noise robust method based on completed local binary patterns for hot-rolled steel strip surface defects. Appl. Surf. Sci. 285, 858\u2013864 (2013)","journal-title":"Appl. Surf. Sci."},{"key":"1885_CR31","unstructured":"Sun, K., Zhao, Y., Jiang, B., Cheng, T., Xiao, B., Liu, D., Mu, Y., Wang, X., Liu, W., Wang, J.: High-resolution representations for labeling pixels and regions. arXiv preprint arXiv:1904.04514 (2019)"},{"issue":"3","key":"1885_CR32","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., Sko\u010daj, D.: Segmentation-based deep-learning approach for surface-defect detection. J. Intell. Manuf. 31(3), 759\u2013776 (2020)","journal-title":"J. Intell. Manuf."},{"key":"1885_CR33","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, pp. 10781\u201310790 (2020)","DOI":"10.1109\/CVPR42600.2020.01079"},{"key":"1885_CR34","doi-asserted-by":"crossref","unstructured":"Tian, Z., Shen, C., Chen, H., He, T.: Fcos: Fully convolutional one-stage object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 9627\u20139636 (2019)","DOI":"10.1109\/ICCV.2019.00972"},{"key":"1885_CR35","first-page":"107984","volume":"37","author":"A Wang","year":"2024","unstructured":"Wang, A., Chen, H., Liu, L., Chen, K., Lin, Z., Han, J., 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":"1885_CR36","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Yeh, I.H., Mark\u00a0Liao, H.Y.: Yolov9: learning what you want to learn using programmable gradient information. In: European Conference on Computer Vision, pp. 1\u201321. Springer (2024)","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"1885_CR37","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\/CVF Conference on Computer Vision And Pattern Recognition, pp. 11534\u201311542 (2020)","DOI":"10.1109\/CVPR42600.2020.01155"},{"key":"1885_CR38","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 (ECCV), pp. 3\u201319 (2018)","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"1885_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, S., Chi, C., Yao, Y., Lei, Z., Li, S.Z.: Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 9759\u20139768 (2020)","DOI":"10.1109\/CVPR42600.2020.00978"},{"key":"1885_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2025.112537","volume":"162","author":"W Zhang","year":"2025","unstructured":"Zhang, W.: Gate-guided spatial-channel reconstruction network: An efficient lightweight framework for steel surface defect detection. Eng. Appl. Artif. Intell. 162, 112537 (2025)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"19","key":"1885_CR41","doi-asserted-by":"publisher","first-page":"12274","DOI":"10.3390\/su141912274","volume":"14","author":"Y Zhang","year":"2022","unstructured":"Zhang, Y., Guo, Z., Wu, J., Tian, Y., Tang, H., Guo, X.: Real-time vehicle detection based on improved yolo v5. Sustainability 14(19), 12274 (2022)","journal-title":"Sustainability"},{"key":"1885_CR42","doi-asserted-by":"crossref","unstructured":"Zhao, Q., Sheng, T., Wang, Y., Tang, Z., Chen, Y., Cai, L., Ling, H.: M2det: a single-shot object detector based on multi-level feature pyramid network. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a033, pp. 9259\u20139266 (2019)","DOI":"10.1609\/aaai.v33i01.33019259"},{"key":"1885_CR43","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, pp. 16965\u201316974 (2024)","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"1885_CR44","doi-asserted-by":"crossref","unstructured":"Zhu, C., He, Y., Savvides, M.: Feature selective anchor-free module for single-shot object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 840\u2013849 (2019)","DOI":"10.1109\/CVPR.2019.00093"}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-026-01885-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11554-026-01885-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-026-01885-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T07:33:11Z","timestamp":1778484791000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11554-026-01885-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":44,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,4]]}},"alternative-id":["1885"],"URL":"https:\/\/doi.org\/10.1007\/s11554-026-01885-1","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"value":"1861-8200","type":"print"},{"value":"1861-8219","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"20 January 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 April 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 April 2026","order":3,"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 no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"86"}}