{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:18:19Z","timestamp":1742912299764,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819712793"},{"type":"electronic","value":"9789819712809"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-1280-9_4","type":"book-chapter","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T06:01:41Z","timestamp":1712037701000},"page":"45-58","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Road Traffic Waterlogging Detection Based on YOLOv5"],"prefix":"10.1007","author":[{"given":"Jianqiang","family":"Liu","sequence":"first","affiliation":[]},{"given":"Yujie","family":"Shang","sequence":"additional","affiliation":[]},{"given":"Xingyao","family":"Li","sequence":"additional","affiliation":[]},{"given":"Huizhen","family":"Hao","sequence":"additional","affiliation":[]},{"given":"Peng","family":"Geng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,4,3]]},"reference":[{"key":"4_CR1","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.habitatint.2017.11.013","volume":"71","author":"T Lin","year":"2018","unstructured":"Lin, T., Liu, X., Song, J., et al.: Urban waterlogging risk assessment based on internet open data: a case study in China. Habitat Int. 71, 88\u201396 (2018)","journal-title":"Habitat Int."},{"key":"4_CR2","doi-asserted-by":"publisher","first-page":"3757","DOI":"10.1007\/s11269-012-0101-6","volume":"26","author":"X Zhang","year":"2012","unstructured":"Zhang, X., Hu, M., Chen, G., et al.: Urban rainwater utilization and its role in mitigating urban waterlogging problems\u2014a case study in Nanjing, China. Water Resour. Manage 26, 3757\u20133766 (2012)","journal-title":"Water Resour. Manage"},{"issue":"5","key":"4_CR3","doi-asserted-by":"publisher","first-page":"587","DOI":"10.3390\/rs11050587","volume":"11","author":"J Jiang","year":"2019","unstructured":"Jiang, J., Liu, J., Cheng, C., et al.: Automatic estimation of urban waterlogging depths from video images based on ubiquitous reference objects. Remote Sens. 11(5), 587 (2019)","journal-title":"Remote Sens."},{"key":"4_CR4","doi-asserted-by":"publisher","unstructured":"Liu, Y., Du, M., Jing, C., Cai, G.: Design and implementation of monitoring and early warning system for urban roads waterlogging. In: Li, D., Chen, Y. (eds.) Computer and Computing Technologies in Agriculture VIII. CCTA 2014. IFIP Advances in Information and Communication Technology, vol. 452, pp. 610\u2013615. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-19620-6_68","DOI":"10.1007\/978-3-319-19620-6_68"},{"key":"4_CR5","doi-asserted-by":"crossref","unstructured":"Redmon, J., Divvala, S., Girshick, R., et al.: 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":"4_CR6","doi-asserted-by":"crossref","unstructured":"Redmon, J., Farhadi, A.: YOLO9000: better, faster, stronger. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7263\u20137271 (2017)","DOI":"10.1109\/CVPR.2017.690"},{"key":"4_CR7","doi-asserted-by":"crossref","unstructured":"Al-Haija, Q.A., Smadi, M., Al-Bataineh, O.M.: Identifying phasic dopamine releases using DarkNet-19 convolutional neural network. In: 2021 IEEE International IoT, Electronics and Mechatronics Conference (IEMTRONICS), pp. 1\u20135. IEEE (2021)","DOI":"10.1109\/IEMTRONICS52119.2021.9422617"},{"key":"4_CR8","unstructured":"Redmon, J., Farhadi, A.: YOLOv3: an incremental improvement. arXiv:1804.02767 (2018)"},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Lin, T.Y., Doll\u00e1r, P., Girshick, R., et al.: 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":"4_CR10","unstructured":"Bochkovskiy, A., Wang, C.Y., Liao, H.YM.: Yolov4: Optimal speed and accuracy of object detection. arXiv preprint arXiv:2004.10934 (2020)"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Wang, C.Y., Liao, H.Y.M., Wu, Y.H., et al. CSPNet: a new backbone that can enhance learning capability of CNN. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 390\u2013391 (2020)","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"4_CR12","doi-asserted-by":"crossref","unstructured":"Shi, X., Hu, J., Lei, X., et al.: Detection of flying birds in airport monitoring based on improved YOLOv5. In: 2021 6th International Conference on Intelligent Computing and Signal Processing (ICSP), pp. 1446\u20131451. IEEE (2021)","DOI":"10.1109\/ICSP51882.2021.9408797"},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Yang, J., Fu, X., Hu, Y., et al.: PanNet: a deep network architecture for pan-sharpening. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 5449\u20135457 (2017)","DOI":"10.1109\/ICCV.2017.193"},{"key":"4_CR14","doi-asserted-by":"crossref","unstructured":"Woo, S., Park, J., Lee, J.Y., et al.: 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":"4_CR15","doi-asserted-by":"crossref","unstructured":"Rezatofighi, H., Tsoi, N., Gwak, J.Y., et al.: Generalized intersection over union: a metric and a loss for bounding box regression. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp. 658\u2013666 (2019)","DOI":"10.1109\/CVPR.2019.00075"},{"key":"4_CR16","doi-asserted-by":"crossref","unstructured":"Yu, J., Jiang, Y., Wang, Z., et al.: Unitbox: an advanced object detection network. In: Proceedings of the 24th ACM International Conference on Multimedia, pp. 516\u2013520 (2016)","DOI":"10.1145\/2964284.2967274"},{"key":"4_CR17","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Wang, P., Liu, W., et al.: Distance-IoU loss: faster and better learning for bounding box regression. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34, no. 07, pp. 12993\u201313000 (2020)","DOI":"10.1609\/aaai.v34i07.6999"}],"container-title":["Communications in Computer and Information Science","Data Science and Information Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-1280-9_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T06:09:47Z","timestamp":1712038187000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-1280-9_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819712793","9789819712809"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-1280-9_4","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IAIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Artificial Intelligence Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iaic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iaicconf.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}