{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:13:14Z","timestamp":1750219994316,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T00:00:00Z","timestamp":1666310400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,10,21]]},"DOI":"10.1145\/3569966.3570099","type":"proceedings-article","created":{"date-parts":[[2022,12,20]],"date-time":"2022-12-20T22:24:41Z","timestamp":1671575081000},"page":"517-521","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["MetaCNN: A New Hybrid Deep Learning Image-based Approach for Vehicle Classification Using Transformer-like Framework"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6438-3296","authenticated-orcid":false,"given":"Juntian","family":"Chen","sequence":"first","affiliation":[{"name":"Tabor Academy, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0939-4275","authenticated-orcid":false,"given":"Ruikang","family":"Luo","sequence":"additional","affiliation":[{"name":"School of Electrical and Electronic Engineering, Nanyang Technological University Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,12,20]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/MVT.2009.935537"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01249-6_42"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.proeng.2017.09.594"},{"key":"e_1_3_2_1_4_1","first-page":"4064","volume-title":"International conference on machine learning. PMLR","author":"Parmar N.","year":"2018","unstructured":"N. Parmar , A. Vaswani , J. Uszkoreit , L. Kaiser , N. Shazeer , A. Ku , and D. Tran , \u201c Image transformer ,\u201d in International conference on machine learning. PMLR , 2018 , pp. 4055\u2013 4064 . N. Parmar, A. Vaswani, J. Uszkoreit, L. Kaiser, N. Shazeer, A. Ku, and D. Tran, \u201cImage transformer,\u201d in International conference on machine learning. PMLR, 2018, pp. 4055\u20134064."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2019.2935152"},{"key":"e_1_3_2_1_6_1","volume-title":"Joint cnn and transformer network via weakly supervised learning for efficient crowd counting","author":"Wang F.","year":"2022","unstructured":"F. Wang , K. Liu , F. Long , N. Sang , X. Xia , and J. Sang , \u201c Joint cnn and transformer network via weakly supervised learning for efficient crowd counting ,\u201d arXiv preprint arXiv:2203.06388, 2022 . F. Wang, K. Liu, F. Long, N. Sang, X. Xia, and J. Sang, \u201cJoint cnn and transformer network via weakly supervised learning for efficient crowd counting,\u201d arXiv preprint arXiv:2203.06388, 2022."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICARCV50220.2020.9305483"},{"volume-title":"Single image haze removal using dark channel prior","author":"He K.","key":"e_1_3_2_1_8_1","unstructured":"K. He , J. Sun , and X. Tang , \u201c Single image haze removal using dark channel prior ,\u201d IEEE transactions on pattern analysis and machine intelligence, vol. 33 , no. 12, pp. 2341\u20132353, 2010. K. He, J. Sun, and X. Tang, \u201cSingle image haze removal using dark channel prior,\u201d IEEE transactions on pattern analysis and machine intelligence, vol. 33, no. 12, pp. 2341\u20132353, 2010."},{"volume-title":"Vehicle type classification using a semisupervised convolutional neural network","author":"Dong Z.","key":"e_1_3_2_1_9_1","unstructured":"Z. Dong , Y. Wu , M. Pei , and Y. Jia , \u201c Vehicle type classification using a semisupervised convolutional neural network ,\u201d IEEE transactions on intelligent transportation systems, vol. 16 , no. 4, pp. 2247\u20132256, 2015. Z. Dong, Y. Wu, M. Pei, and Y. Jia, \u201cVehicle type classification using a semisupervised convolutional neural network,\u201d IEEE transactions on intelligent transportation systems, vol. 16, no. 4, pp. 2247\u20132256, 2015."},{"key":"e_1_3_2_1_10_1","volume-title":"An image is worth 16x16 words: Transformers for image recognition at scale","author":"Dosovitskiy A.","year":"2010","unstructured":"A. Dosovitskiy , L. Beyer , A. Kolesnikov , D. Weissenborn , X. Zhai , T. Unterthiner , M. Dehghani , M. Minderer , G. Heigold , S. Gelly , \u201c An image is worth 16x16 words: Transformers for image recognition at scale ,\u201d arXiv preprint arXiv: 2010 .11929, 2020. A. Dosovitskiy, L. Beyer, A. Kolesnikov, D. Weissenborn, X. Zhai, T. Unterthiner, M. Dehghani, M. Minderer, G. Heigold, S. Gelly , \u201cAn image is worth 16x16 words: Transformers for image recognition at scale,\u201d arXiv preprint arXiv:2010.11929, 2020."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01055"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.05.069"},{"key":"e_1_3_2_1_13_1","volume-title":"Deep learning using rectified linear units (relu)","author":"Agarap A. F.","year":"1803","unstructured":"A. F. Agarap , \u201c Deep learning using rectified linear units (relu) ,\u201d arXiv preprint arXiv: 1803 .08375, 2018. A. F. Agarap, \u201cDeep learning using rectified linear units (relu),\u201d arXiv preprint arXiv:1803.08375, 2018."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.3390\/rs13030516"},{"key":"e_1_3_2_1_15_1","volume-title":"Metaformer: A unified meta framework for fine-grained recognition","author":"Diao Q.","year":"2022","unstructured":"Q. Diao , Y. Jiang , B. Wen , J. Sun , and Z. Yuan , \u201c Metaformer: A unified meta framework for fine-grained recognition ,\u201d arXiv preprint arXiv:2203.02751, 2022 . Q. Diao, Y. Jiang, B. Wen, J. Sun, and Z. Yuan, \u201cMetaformer: A unified meta framework for fine-grained recognition,\u201d arXiv preprint arXiv:2203.02751, 2022."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46487-9_48"}],"event":{"name":"CSSE 2022: 2022 5th International Conference on Computer Science and Software Engineering","acronym":"CSSE 2022","location":"Guilin China"},"container-title":["Proceedings of the 5th International Conference on Computer Science and Software Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569966.3570099","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3569966.3570099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:37Z","timestamp":1750182577000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3569966.3570099"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,21]]},"references-count":16,"alternative-id":["10.1145\/3569966.3570099","10.1145\/3569966"],"URL":"https:\/\/doi.org\/10.1145\/3569966.3570099","relation":{},"subject":[],"published":{"date-parts":[[2022,10,21]]},"assertion":[{"value":"2022-12-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}