{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T11:06:20Z","timestamp":1770462380556,"version":"3.49.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T00:00:00Z","timestamp":1765324800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T00:00:00Z","timestamp":1765324800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"High-performance Computing Platform of China University of Geosciences Beijing"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Real-Time Image Proc"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1007\/s11554-025-01812-w","type":"journal-article","created":{"date-parts":[[2025,12,10]],"date-time":"2025-12-10T17:42:27Z","timestamp":1765388547000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["HAS-DETR: a real-time lightweight traffic sign detection model"],"prefix":"10.1007","volume":"23","author":[{"given":"Junhao","family":"Dong","sequence":"first","affiliation":[]},{"given":"Hongxiang","family":"Liao","sequence":"additional","affiliation":[]},{"given":"Xiaohui","family":"Ji","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,10]]},"reference":[{"issue":"3","key":"1812_CR1","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/s13735-017-0129-8","volume":"6","author":"Y Saadna","year":"2017","unstructured":"Saadna, Y., Behloul, A.: An overview of traffic sign detection and classification methods. Int. J. Multimedia Inform. Retrieval 6(3), 193\u2013210 (2017)","journal-title":"Int. J. Multimedia Inform. Retrieval"},{"key":"1812_CR2","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Liang, D., Zhang, S., Huang, X., Li, B., Hu, S.: Traffic-sign detection and classification in the wild. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 2110\u20132118 (2016)","DOI":"10.1109\/CVPR.2016.232"},{"issue":"6","key":"1812_CR3","doi-asserted-by":"publisher","first-page":"1388","DOI":"10.1108\/JEDT-02-2021-0101","volume":"20","author":"DJ Edwards","year":"2022","unstructured":"Edwards, D.J., Akhtar, J., Rillie, I., Chileshe, N., Lai, J.H., Roberts, C.J., Ejohwomu, O.: Systematic analysis of driverless technologies. J. Eng. Design Technol. 20(6), 1388\u20131411 (2022)","journal-title":"J. Eng. Design Technol."},{"issue":"7","key":"1812_CR4","doi-asserted-by":"publisher","first-page":"2022","DOI":"10.1109\/TITS.2015.2482461","volume":"17","author":"Y Yang","year":"2015","unstructured":"Yang, Y., Luo, H., Xu, H., Wu, F.: Towards real-time traffic sign detection and classification. IEEE Trans. Intell. Transp. Syst. 17(7), 2022\u20132031 (2015)","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"issue":"7","key":"1812_CR5","doi-asserted-by":"publisher","first-page":"2300706","DOI":"10.1002\/aisy.202300706","volume":"6","author":"S Ul Amin","year":"2024","unstructured":"Ul Amin, S., Kim, B., Jung, Y., Seo, S., Park, S.: Video anomaly detection utilizing efficient spatiotemporal feature fusion with 3d convolutions and long short-term memory modules. Adv. Intell. Syst. 6(7), 2300706 (2024)","journal-title":"Adv. Intell. Syst."},{"key":"1812_CR6","doi-asserted-by":"crossref","unstructured":"Liu, X., Chu, R., Liu, B.: Tfg-net: a text feature-guided network for small traffic sign detection. In: IEEE Transactions on Neural Networks and Learning Systems (2024)","DOI":"10.1109\/TNNLS.2024.3454063"},{"key":"1812_CR7","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: European conference on computer vision, pp. 213\u2013229. Springer (2020)","DOI":"10.1007\/978-3-030-58452-8_13"},{"key":"1812_CR8","unstructured":"Zhu, X., Su,W., Lu, L., Li, B., Wang, X., Dai, J.: Deformable detr: Deformable transformers for end-to-end object detection. arXiv:2010.04159. (2020)"},{"key":"1812_CR9","unstructured":"Yao, Z., Ai, J., Li, B., Zhang, C.: Efficient detr: improving end-to-end object detector with dense prior. arXiv:2104.01318. (2021)"},{"key":"1812_CR10","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. 16\u00a0965\u201316\u00a0974 (2024)","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"1812_CR11","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":"1812_CR12","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":"1812_CR13","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 Inform. Process. Syst.\u00a030 (2017)"},{"key":"1812_CR14","volume-title":"An overview of traffic sign detection methods, Zagreb: Department of Electronics","author":"K Brkic","year":"2010","unstructured":"Brkic, K.: An overview of traffic sign detection methods, Zagreb: Department of Electronics. Microelectronics, Computer and Intelligent Systems, Faculty of Electrical Engineering and Computing (2010)"},{"key":"1812_CR15","doi-asserted-by":"crossref","unstructured":"Liu, C., Li, S., Chang, F., Wang, Y.: Machine vision based traffic sign detection methods: Review, analyses and perspectives. IEEE Access, vol.\u00a07, pp. 86\u00a0578\u201386\u00a0596 (2019)","DOI":"10.1109\/ACCESS.2019.2924947"},{"key":"1812_CR16","unstructured":"Sermanet, P., Eigen, D., Zhang, X., Mathieu, M., Fergus, R., LeCun, Y.: Overfeat: Integrated recognition, localization and detection using convolutional networks. arXiv:1312.6229 (2013)"},{"key":"1812_CR17","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"},{"key":"1812_CR18","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"},{"issue":"6","key":"1812_CR19","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","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. 39(6), 1137\u20131149 (2016)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1812_CR20","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"},{"issue":"3","key":"1812_CR21","first-page":"2567","volume":"36","author":"Y Wang","year":"2022","unstructured":"Wang, Y., Zhang, X., Yang, T., Sun, J.: Anchor detr: Query design for transformer-based detector. Proc. AAAI Confer. Artif. Intell. 36(3), 2567\u20132575 (2022)","journal-title":"Proc. AAAI Confer. Artif. Intell."},{"key":"1812_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2025.111655","volume":"159","author":"SU Amin","year":"2025","unstructured":"Amin, S.U., Jung, Y., Fayaz, M., Kim, B., Seo, S.: Enhancing pine wilt disease detection with synthetic data and external attention-based transformers. Eng. Appl. Artif. Intell. 159, 111655 (2025)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"1812_CR23","doi-asserted-by":"crossref","unstructured":"Yao, T., Li, Y., Pan, Y., Mei, T.: Hgnet: learning hierarchical geometry from points, edges, and surfaces. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 21\u00a0846\u201321\u00a0855 (2023)","DOI":"10.1109\/CVPR52729.2023.02092"},{"key":"1812_CR24","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"1812_CR25","unstructured":"Bochkovskiy, A., Wang, C.-Y., Liao, H.-Y.M.: Yolov4: optimal speed and accuracy of object detection. arXiv:2004.10934 (2020)"},{"key":"1812_CR26","unstructured":"Li, A., Zhang, L., Liu, Y., Zhu, C.: Feature modulation transformer: Cross-refinement of global representation via high-frequency prior for image super-resolution. In: Proceedings of the IEEE\/CVF international conference on computer vision, pp. 12\u00a0514\u201312\u00a0524 (2023)"},{"key":"1812_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2024.105057","volume":"147","author":"M Kang","year":"2024","unstructured":"Kang, M., Ting, C.-M., Ting, F.F., Phan, R.C.-W.: Asf-yolo: a novel yolo model with attentional scale sequence fusion for cell instance segmentation. Image Vis. Comput. 147, 105057 (2024)","journal-title":"Image Vis. Comput."},{"key":"1812_CR28","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":"1812_CR29","unstructured":"Zhang, J., Zou, X., Kuang, L.-D., Wang, J., Sherratt, R.S., Yu, X.: Cctsdb: a more comprehensive traffic sign detection benchmark. HCIS 12, 2022 (2021)"},{"key":"1812_CR30","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":"1812_CR31","unstructured":"Wang, A., Chen, H., Liu, L., Chen, K., Lin, Z., Han, J., et\u00a0al.: Yolov10: real-time end-to-end object detection. Adv. Neural Inform. Process. Syst. 37, 107\u00a0984\u2013108\u00a0011 (2024)"}],"container-title":["Journal of Real-Time Image Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-025-01812-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11554-025-01812-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11554-025-01812-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T16:49:46Z","timestamp":1770396586000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11554-025-01812-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,10]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["1812"],"URL":"https:\/\/doi.org\/10.1007\/s11554-025-01812-w","relation":{},"ISSN":["1861-8200","1861-8219"],"issn-type":[{"value":"1861-8200","type":"print"},{"value":"1861-8219","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,10]]},"assertion":[{"value":"14 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2025","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":"25"}}