{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:22:22Z","timestamp":1783938142938,"version":"3.55.0"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T00:00:00Z","timestamp":1737072000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T00:00:00Z","timestamp":1737072000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62171042, 62102033"],"award-info":[{"award-number":["62171042, 62102033"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62171042, 62102033"],"award-info":[{"award-number":["62171042, 62102033"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Beijing Municipal Key Science and Technology Project","award":["KZ202211417048"],"award-info":[{"award-number":["KZ202211417048"]}]},{"name":"Beijing Municipal Key Science and Technology Project","award":["KZ202211417048"],"award-info":[{"award-number":["KZ202211417048"]}]},{"name":"Support Programme for High-level Scientific Research and Innovation Teams of Higher Educational Institutions under Beijing Municipality","award":["BPHR20220121"],"award-info":[{"award-number":["BPHR20220121"]}]},{"name":"Support Programme for High-level Scientific Research and Innovation Teams of Higher Educational Institutions under Beijing Municipality","award":["BPHR20220121"],"award-info":[{"award-number":["BPHR20220121"]}]},{"name":"Beijing Union University Project","award":["ZKZD202302"],"award-info":[{"award-number":["ZKZD202302"]}]},{"name":"Beijing Union University Project","award":["ZKZD202302"],"award-info":[{"award-number":["ZKZD202302"]}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["2022YFC3090603"],"award-info":[{"award-number":["2022YFC3090603"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimedia Systems"],"published-print":{"date-parts":[[2025,4]]},"DOI":"10.1007\/s00530-024-01661-w","type":"journal-article","created":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T05:39:11Z","timestamp":1737092351000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Flood scenarios vehicle detection algorithm based on improved YOLOv9"],"prefix":"10.1007","volume":"31","author":[{"given":"Jiwu","family":"Sun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yujia","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengfei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongzhe","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,17]]},"reference":[{"key":"1661_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2023.104208","volume":"100","author":"X Wang","year":"2024","unstructured":"Wang, X., Chen, W., Yin, J., et al.: Risk assessment of flood disasters in the Poyang lake area. Int. J. Dis. Risk Reduct. 100, 104208 (2024)","journal-title":"Int. J. Dis. Risk Reduct."},{"key":"1661_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2024.104249","volume":"101","author":"H Li","year":"2024","unstructured":"Li, H., Han, Y., Wang, X., et al.: Risk perception and resilience assessment of flood disasters based on social media big data. Int. J. Dis. Risk Reduct. 101, 104249 (2024)","journal-title":"Int. J. Dis. Risk Reduct."},{"key":"1661_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.envint.2020.106236","volume":"146","author":"C Tonne","year":"2021","unstructured":"Tonne, C., Adair, L., Adlakha, D., et al.: Defining pathways to healthy sustainable urban development. Environ. Int. 146, 106236 (2021)","journal-title":"Environ. Int."},{"issue":"07","key":"1661_CR4","first-page":"757","volume":"53","author":"X Cheng","year":"2022","unstructured":"Cheng, X., Liu, C., Li, C., et al.: Characteristics of flood risk evolution and urban resilience enhancement strategies in changing environments. J. Water Res. 53(07), 757\u2013768+778 (2022)","journal-title":"J. Water Res."},{"issue":"11","key":"1661_CR5","first-page":"1107","volume":"38","author":"X Zongxue","year":"2023","unstructured":"Zongxue, X., Ye, C., Liao, R.: Collaborative management of urban flooding: research progress and application cases. Adv. Earth Sci. 38(11), 1107\u20131120 (2023)","journal-title":"Adv. Earth Sci."},{"issue":"7","key":"1661_CR6","doi-asserted-by":"publisher","first-page":"141","DOI":"10.3390\/hydrology10070141","volume":"10","author":"V Kumar","year":"2023","unstructured":"Kumar, V., Sharma, K.V., Caloiero, T., et al.: Comprehensive Overview of Flood Modeling Approaches: A Review of Recent Advances. Hydrology 10(7), 141 (2023)","journal-title":"Hydrology"},{"key":"1661_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eiar.2023.107319","volume":"104","author":"L Peng","year":"2024","unstructured":"Peng, L., Wang, Y., Yang, L., et al.: A comparative analysis on flood risk assessment and management performances between Beijing and Munich. Environ. Impact Assess. Rev. 104, 107319 (2024)","journal-title":"Environ. Impact Assess. Rev."},{"issue":"1","key":"1661_CR8","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1109\/JSEN.2022.3223671","volume":"23","author":"C Prakash","year":"2022","unstructured":"Prakash, C., Barthwal, A., Acharya, D.: FLOODWALL: A Real-Time Flash Flood Monitoring and Forecasting System Using IoT. IEEE Sensors J. 23(1), 787\u2013799 (2022)","journal-title":"IEEE Sensors J."},{"key":"1661_CR9","doi-asserted-by":"crossref","unstructured":"Mansour, R.F., Alabdulkreem, E.: Disaster Monitoring of Satellite Image Processing Using Progressive Image Classification. Computer Syst. Sci. & Eng. 44(2), (2023)","DOI":"10.32604\/csse.2023.023307"},{"issue":"14","key":"1661_CR10","doi-asserted-by":"publisher","first-page":"2207","DOI":"10.3390\/w14142207","volume":"14","author":"T Lei","year":"2022","unstructured":"Lei, T., Wang, J., Li, X., et al.: Flood disaster monitoring and emergency assessment based on multi-source remote sensing observations. Water 14(14), 2207 (2022)","journal-title":"Water"},{"issue":"3","key":"1661_CR11","doi-asserted-by":"publisher","first-page":"3123","DOI":"10.1007\/s11069-022-05508-3","volume":"114","author":"Z Wang","year":"2022","unstructured":"Wang, Z., Gao, Z.: Dynamic monitoring of flood disaster based on remote sensing data cube. Nat. Hazards 114(3), 3123\u20133138 (2022)","journal-title":"Nat. Hazards"},{"key":"1661_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118992","volume":"213","author":"P Deshmukh","year":"2023","unstructured":"Deshmukh, P., Satyanarayana, G.S.R., Majhi, S., et al.: Swin transformer based vehicle detection in undisciplined traffic environment. Expert Syst. Appl. 213, 118992 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"1661_CR13","doi-asserted-by":"publisher","first-page":"2609","DOI":"10.1007\/s00521-022-07717-0","volume":"35","author":"F Alam","year":"2023","unstructured":"Alam, F., Alam, T., Hasan, M.A., et al.: MEDIC: a multi-task learning dataset for disaster image classification. Neural Comput. Appl. 35(3), 2609\u20132632 (2023)","journal-title":"Neural Comput. Appl."},{"issue":"1","key":"1661_CR14","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/s00530-023-01228-1","volume":"30","author":"J Yuan","year":"2024","unstructured":"Yuan, J., Hu, Y., Sun, Y., et al.: A plug-and-play image enhancement model for end-to-end object detection in low-light condition. Multimed. Syst. 30(1), 27 (2024)","journal-title":"Multimed. Syst."},{"issue":"1","key":"1661_CR15","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1007\/s40747-022-00786-7","volume":"9","author":"X Li","year":"2023","unstructured":"Li, X., He, M., Liu, Y., et al.: SPCS: a spatial pyramid convolutional shuffle module for YOLO to detect occluded object. Complex & Int. Syst. 9(1), 301\u2013315 (2023)","journal-title":"Complex & Int. Syst."},{"issue":"19","key":"1661_CR16","doi-asserted-by":"publisher","first-page":"7294","DOI":"10.3390\/s22197294","volume":"22","author":"L Hou","year":"2022","unstructured":"Hou, L., Chen, C., Wang, S., et al.: Multi-object detection method in construction machinery swarm operations based on the improved YOLOv4 model. Sensors 22(19), 7294 (2022)","journal-title":"Sensors"},{"issue":"5","key":"1661_CR17","doi-asserted-by":"publisher","first-page":"2591","DOI":"10.1007\/s00530-023-01116-8","volume":"29","author":"W Gao","year":"2023","unstructured":"Gao, W., Zhang, Y., Long, W., et al.: A deraining with detail-recovery network via context aggregation. Multimed. Syst. 29(5), 2591\u20132601 (2023)","journal-title":"Multimed. Syst."},{"key":"1661_CR18","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.patrec.2024.01.006","volume":"178","author":"N Zhou","year":"2024","unstructured":"Zhou, N., Deng, J., Pang, M.: Recovering a clean background: A parallel deep network architecture for single-image deraining. Pattern Recogn. Lett. 178, 153\u2013159 (2024)","journal-title":"Pattern Recogn. Lett."},{"key":"1661_CR19","doi-asserted-by":"crossref","unstructured":"Zhao, H., Zhang, H., Zhao, Y.: Yolov7-sea: Object detection of maritime uav images based on improved yolov7[C]\/\/Proceedings of the IEEE\/CVF winter conference on applications of computer vision. p. 233\u2013238 (2023)","DOI":"10.1109\/WACVW58289.2023.00029"},{"key":"1661_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119108","volume":"213","author":"M Bie","year":"2023","unstructured":"Bie, M., Liu, Y., Li, G., et al.: Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach. Expert Syst. Appl. 213, 119108 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"8","key":"1661_CR21","doi-asserted-by":"publisher","first-page":"2394","DOI":"10.3390\/s24082394","volume":"24","author":"D Huang","year":"2024","unstructured":"Huang, D., Tu, Y., Zhang, Z., et al.: A lightweight vehicle detection method fusing GSConv and coordinate attention mechanism. Sensors 24(8), 2394 (2024)","journal-title":"Sensors"},{"issue":"3","key":"1661_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11554-024-01457-1","volume":"21","author":"JL Andika","year":"2024","unstructured":"Andika, J.L., Khairuddin, A.S.M., Ramiah, H., et al.: Improved feature extraction network in lightweight YOLOv7 model for real-time vehicle detection on low-cost hardware. J. Real-Time Image Process. 21(3), 1\u201312 (2024)","journal-title":"J. Real-Time Image Process."},{"key":"1661_CR23","doi-asserted-by":"crossref","unstructured":"Hoanh, N., Pham, T.V.: A multi-task framework for car detection from high-resolution uav imagery focusing on road regions. IEEE Trans. Intell. Transp. Syst. (2024)","DOI":"10.1109\/TITS.2024.3432761"},{"key":"1661_CR24","doi-asserted-by":"crossref","unstructured":"Ying, Z., Zhou, J., Zhai, Y., et al.: Large-Scale High-Altitude UAV-Based Vehicle Detection via Pyramid Dual Pooling Attention Path Aggregation Network. IEEE Trans. Intell. Transp. Syst. (2024)","DOI":"10.1109\/TITS.2024.3396915"},{"issue":"5","key":"1661_CR25","doi-asserted-by":"publisher","first-page":"93","DOI":"10.1007\/s11554-023-01344-1","volume":"20","author":"MK Alam","year":"2023","unstructured":"Alam, M.K., Ahmed, A., Salih, R., et al.: Faster RCNN based robust vehicle detection algorithm for identifying and classifying vehicles. J. Real-Time Image Process. 20(5), 93 (2023)","journal-title":"J. Real-Time Image Process."},{"issue":"19","key":"1661_CR26","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., et al.: Real-time vehicle detection based on improved yolo v5. Sustainability 14(19), 12274 (2022)","journal-title":"Sustainability"},{"key":"1661_CR27","doi-asserted-by":"publisher","first-page":"104914","DOI":"10.1016\/j.engappai.2022.104914","volume":"113","author":"X Dong","year":"2022","unstructured":"Dong, X., Yan, S., Duan, C.: A lightweight vehicles detection network model based on YOLOv5. Eng. Appl. Artif. Intell. 113, 104914 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"key":"1661_CR28","doi-asserted-by":"crossref","unstructured":"Pratama, V., Sukoco, A., Pebriadi, P., et\u00a0al.: Car Detection over Network using Yolov8 in Forza Horizon 4[C]\/\/2023 17th International Conference on Telecommunication Systems, Services, and Applications (TSSA). IEEE, 1\u20135 (2023)","DOI":"10.1109\/TSSA59948.2023.10366964"},{"key":"1661_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2022.111655","volume":"201","author":"Z Chen","year":"2022","unstructured":"Chen, Z., Guo, H., Yang, J., et al.: Fast vehicle detection algorithm in traffic scene based on improved SSD. Measurement 201, 111655 (2022)","journal-title":"Measurement"},{"issue":"6","key":"1661_CR30","doi-asserted-by":"publisher","first-page":"4755","DOI":"10.1007\/s00521-022-07940-9","volume":"35","author":"U Mittal","year":"2023","unstructured":"Mittal, U., Chawla, P., Tiwari, R.: EnsembleNet: A hybrid approach for vehicle detection and estimation of traffic density based on faster R-CNN and YOLO models. Neural Comput. Appl. 35(6), 4755\u20134774 (2023)","journal-title":"Neural Comput. Appl."},{"key":"1661_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.rse.2020.111664","volume":"240","author":"B DeVries","year":"2020","unstructured":"DeVries, B., Huang, C., Armston, J., et al.: Rapid and robust monitoring of flood events using Sentinel-1 and Landsat data on the Google Earth Engine. Remote Sens. Environ. 240, 111664 (2020)","journal-title":"Remote Sens. Environ."},{"key":"1661_CR32","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 (2024). arXiv preprint arXiv:2402.13616","DOI":"10.1007\/978-3-031-72751-1_1"},{"key":"1661_CR33","doi-asserted-by":"crossref","unstructured":"Li, X., Wang, W., Hu, X., Yang, J.: Selective kernel networks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition p. 510\u2013519 (2019)","DOI":"10.1109\/CVPR.2019.00060"},{"key":"1661_CR34","doi-asserted-by":"crossref","unstructured":"Nascimento, M.G.D., Fawcett, R., Prisacariu, V.A.: Dsconv: Efficient convolution operator. In: Proceedings of the IEEE\/CVF international conference on computer vision, p. 5148\u20135157 (2019)","DOI":"10.1109\/ICCV.2019.00525"},{"issue":"11","key":"1661_CR35","doi-asserted-by":"publisher","first-page":"1231","DOI":"10.1177\/0278364913491297","volume":"32","author":"A Geiger","year":"2013","unstructured":"Geiger, A., Lenz, P., Stiller, C., et al.: Vision meets robotics: The kitti dataset. Int. J. Robot. Res. 32(11), 1231\u20131237 (2013)","journal-title":"Int. J. Robot. Res."},{"key":"1661_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2020.102907","volume":"193","author":"L Wen","year":"2020","unstructured":"Wen, L., Du, D., Cai, Z., et al.: UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking. Comput. Vision Image Understand 193, 102907 (2020)","journal-title":"Comput. Vision Image Understand"},{"issue":"1","key":"1661_CR37","doi-asserted-by":"publisher","first-page":"9711","DOI":"10.1038\/s41598-023-36868-w","volume":"13","author":"X Jia","year":"2023","unstructured":"Jia, X., Tong, Y., Qiao, H., et al.: Fast and accurate object detector for autonomous driving based on improved YOLOv5. Sci. Rep. 13(1), 9711 (2023)","journal-title":"Sci. Rep."},{"key":"1661_CR38","unstructured":"Ren, S., He, K., Girshick, R., et\u00a0al.: Faster r-cnn: Towards real-time object detection with region proposal networks. Adv. Neural Inf. Process. Syst. 28, (2015)"},{"issue":"5","key":"1661_CR39","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1109\/TPAMI.2019.2956516","volume":"43","author":"Z Cai","year":"2019","unstructured":"Cai, Z., Vasconcelos, N.: Cascade R-CNN: High quality object detection and instance segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 43(5), 1483\u20131498 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1661_CR40","doi-asserted-by":"crossref","unstructured":"He, K., Gkioxari, G., Doll\u00e1r, P., et\u00a0al.: Mask r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. p. 2961\u20132969 (2017)","DOI":"10.1109\/ICCV.2017.322"},{"issue":"237","key":"1661_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121209","volume":"1","author":"L Kang","year":"2024","unstructured":"Kang, L., Lu, Z., Meng, L., Gao, Z.: YOLO-FA: Type-1 fuzzy attention based YOLO detector for vehicle detection. Expert Syst. Appl. 1(237), 121209 (2024)","journal-title":"Expert Syst. Appl."},{"issue":"213","key":"1661_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.119108","volume":"1","author":"M Bie","year":"2023","unstructured":"Bie, M., Liu, Y., Li, G., Hong, J., Li, J.: Real-time vehicle detection algorithm based on a lightweight You-Only-Look-Once (YOLOv5n-L) approach. Expert Syst. Appl. 1(213), 119108 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"113","key":"1661_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.104914","volume":"1","author":"X Dong","year":"2022","unstructured":"Dong, X., Yan, S., Duan, C.: A lightweight vehicles detection network model based on YOLOv5. Eng. Appl. Artif. Intell. 1(113), 104914 (2022)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"2","key":"1661_CR44","doi-asserted-by":"publisher","first-page":"724","DOI":"10.3390\/s23020724","volume":"23","author":"J Wang","year":"2023","unstructured":"Wang, J., Dong, Y., Zhao, S., Zhang, Z.: A High-Precision Vehicle Detection and Tracking Method Based on the Attention Mechanism. Sensors 23(2), 724 (2023)","journal-title":"Sensors"}],"container-title":["Multimedia Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-024-01661-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00530-024-01661-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00530-024-01661-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T19:33:09Z","timestamp":1745263989000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00530-024-01661-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,17]]},"references-count":44,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["1661"],"URL":"https:\/\/doi.org\/10.1007\/s00530-024-01661-w","relation":{},"ISSN":["0942-4962","1432-1882"],"issn-type":[{"value":"0942-4962","type":"print"},{"value":"1432-1882","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,17]]},"assertion":[{"value":"10 May 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 December 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 January 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"74"}}