{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:14:48Z","timestamp":1750220088228,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":23,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,3,18]],"date-time":"2022-03-18T00:00:00Z","timestamp":1647561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"the Opening Project of Key Laboratory of operation safety technology on transport vehicles ?Ministry of Transport, PRC","award":["2020-8405"],"award-info":[{"award-number":["2020-8405"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,3,18]]},"DOI":"10.1145\/3532213.3532267","type":"proceedings-article","created":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T13:29:18Z","timestamp":1657718958000},"page":"363-367","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Semantic-Based Deep Learning Algorithm for Vehicle Re-identification"],"prefix":"10.1145","author":[{"given":"Xinlei","family":"Wei","sequence":"first","affiliation":[{"name":"Key Laboratory of Operation Safety Technology on Transport Vehicles, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yexuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"Tianjin Normal University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luyao","family":"Wang","sequence":"additional","affiliation":[{"name":"Tianjin Normal University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chengrui","family":"Li","sequence":"additional","affiliation":[{"name":"Tianjin Polytechnic University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Guo","sequence":"additional","affiliation":[{"name":"Tianjin Normal University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,7,13]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2902112"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2016.2639020"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2496545"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Zhou Y Shao L. Aware attentive multi-view inference for vehicle re-identification[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 6489-6498.  Zhou Y Shao L. Aware attentive multi-view inference for vehicle re-identification[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 6489-6498.","DOI":"10.1109\/CVPR.2018.00679"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2019.2927353"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"crossref","unstructured":"Yan K Tian Y Wang Y Exploiting multi-grain ranking constraints for precisely searching visually-similar vehicles[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 562-570.  Yan K Tian Y Wang Y Exploiting multi-grain ranking constraints for precisely searching visually-similar vehicles[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 562-570.","DOI":"10.1109\/ICCV.2017.68"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2019.03.001"},{"key":"e_1_3_2_1_8_1","first-page":"774","article-title":"Fast extraction of traffic parameters and reidentification of vehicles from video data[C]\/\/Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems","volume":"1","author":"Woesler R","year":"2003","unstructured":"Woesler R . Fast extraction of traffic parameters and reidentification of vehicles from video data[C]\/\/Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems . IEEE , 2003 , 1 : 774 - 778 . Woesler R. Fast extraction of traffic parameters and reidentification of vehicles from video data[C]\/\/Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems. IEEE, 2003, 1: 774-778.","journal-title":"IEEE"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"crossref","unstructured":"Liu H Tian Y Yang Y Deep relative distance learning: Tell the difference between similar vehicles[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 2167-2175.  Liu H Tian Y Yang Y Deep relative distance learning: Tell the difference between similar vehicles[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 2167-2175.","DOI":"10.1109\/CVPR.2016.238"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"crossref","unstructured":"Zhou Y Shao L. Aware attentive multi-view inference for vehicle re-identification[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 6489-6498.  Zhou Y Shao L. Aware attentive multi-view inference for vehicle re-identification[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 6489-6498.","DOI":"10.1109\/CVPR.2018.00679"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"crossref","unstructured":"Wang Z Tang L Liu X Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification[C]\/\/Proceedings of the IEEE International Conference on Computer Vision. 2017: 379-387.  Wang Z Tang L Liu X Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification[C]\/\/Proceedings of the IEEE International Conference on Computer Vision. 2017: 379-387.","DOI":"10.1109\/ICCV.2017.49"},{"key":"e_1_3_2_1_12_1","volume-title":"a region-aware deep model for vehicle re-identification[C]\/\/2018 IEEE International Conference on Multimedia and Expo (ICME)","author":"Liu X","year":"2018","unstructured":"Liu X , Zhang S , Huang Q , Ram : a region-aware deep model for vehicle re-identification[C]\/\/2018 IEEE International Conference on Multimedia and Expo (ICME) . IEEE , 2018 : 1-6. Liu X, Zhang S, Huang Q, Ram: a region-aware deep model for vehicle re-identification[C]\/\/2018 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2018: 1-6."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2751966"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"He K Gkioxari G Doll\u00e1r P Mask r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 2961-2969.  He K Gkioxari G Doll\u00e1r P Mask r-cnn[C]\/\/Proceedings of the IEEE international conference on computer vision. 2017: 2961-2969.","DOI":"10.1109\/ICCV.2017.322"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"crossref","unstructured":"He K Zhang X Ren S Deep residual learning for image recognition[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 770-778.  He K Zhang X Ren S Deep residual learning for image recognition[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 770-778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.238"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"crossref","unstructured":"Liu H Tian Y Yang Y Deep relative distance learning: Tell the difference between similar vehicles[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 2167-2175.  Liu H Tian Y Yang Y Deep relative distance learning: Tell the difference between similar vehicles[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 2016: 2167-2175.","DOI":"10.1109\/CVPR.2016.238"},{"key":"e_1_3_2_1_19_1","volume-title":"a region-aware deep model for vehicle re-identification[C]\/\/2018 IEEE International Conference on Multimedia and Expo (ICME)","author":"Liu X","year":"2018","unstructured":"Liu X , Zhang S , Huang Q , Ram : a region-aware deep model for vehicle re-identification[C]\/\/2018 IEEE International Conference on Multimedia and Expo (ICME) . IEEE , 2018 : 1-6. Liu X, Zhang S, Huang Q, Ram: a region-aware deep model for vehicle re-identification[C]\/\/2018 IEEE International Conference on Multimedia and Expo (ICME). IEEE, 2018: 1-6."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2796240"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2902112"},{"key":"e_1_3_2_1_22_1","first-page":"4005","volume-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","author":"Bing He","year":"2019","unstructured":"Bing He , Jia Li, Yifan Zhao , and Yonghong Tian. Partregularized near-duplicate vehicle re-identification . In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , pages 3997\u2013 4005 , 2019 Bing He, Jia Li, Yifan Zhao, and Yonghong Tian. Partregularized near-duplicate vehicle re-identification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 3997\u20134005, 2019"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Wang Z Tang L Liu X Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification[C]\/\/Proceedings of the IEEE International Conference on Computer Vision. 2017: 379-387.  Wang Z Tang L Liu X Orientation invariant feature embedding and spatial temporal regularization for vehicle re-identification[C]\/\/Proceedings of the IEEE International Conference on Computer Vision. 2017: 379-387.","DOI":"10.1109\/ICCV.2017.49"}],"event":{"name":"ICCAI '22: 2022 8th International Conference on Computing and Artificial Intelligence","acronym":"ICCAI '22","location":"Tianjin China"},"container-title":["Proceedings of the 8th International Conference on Computing and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3532213.3532267","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3532213.3532267","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T18:09:43Z","timestamp":1750183783000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3532213.3532267"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,18]]},"references-count":23,"alternative-id":["10.1145\/3532213.3532267","10.1145\/3532213"],"URL":"https:\/\/doi.org\/10.1145\/3532213.3532267","relation":{},"subject":[],"published":{"date-parts":[[2022,3,18]]},"assertion":[{"value":"2022-07-13","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}