{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:27:06Z","timestamp":1750220826831,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":8,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,10,15]],"date-time":"2019-10-15T00:00:00Z","timestamp":1571097600000},"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":[[2019,10,15]]},"DOI":"10.1145\/3343031.3356079","type":"proceedings-article","created":{"date-parts":[[2019,10,21]],"date-time":"2019-10-21T16:32:26Z","timestamp":1571675546000},"page":"2588-2592","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Biomedia ACM MM Grand Challenge 2019"],"prefix":"10.1145","author":[{"given":"Wenhua","family":"Meng","sequence":"first","affiliation":[{"name":"ZhengZhou University, ZhengZhou, China"}]},{"given":"Shan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Union University, Beijing, China"}]},{"given":"Xudong","family":"Yao","sequence":"additional","affiliation":[{"name":"Chinese Academy of Sciences, Beijing, China"}]},{"given":"Xiaoshan","family":"Yang","sequence":"additional","affiliation":[{"name":"NLPR, CASIA &amp; Peng Cheng Laboratory, Beijing, China"}]},{"given":"Changsheng","family":"Xu","sequence":"additional","affiliation":[{"name":"NLPR, CASIA &amp; Peng Cheng Laboratory, Beijing, China"}]},{"given":"Xiaowen","family":"Huang","sequence":"additional","affiliation":[{"name":"NLPR, CASIA &amp; University of Chinese Academy of Sciences, Beijing, China"}]}],"member":"320","published-online":{"date-parts":[[2019,10,15]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"ACM MM BioMedia 2019 Grand Challenge Overview. In: Proceedings of the ACM International Conference on Multimedia (ACM MM'19), ACM","author":"Hicks Steven","year":"2019","unstructured":"Steven Hicks , Michael Riegler , Pia Smedsrud , Trine B. Haugen , Kristin Randheim Randel , Konstantin Pogorelov , H\u00e5kon Kvale Stensland , Duc-Tien Dang-Nguyen , Mathias Lux , Andreas Petlund , Thomas de Lange , Peter Thelin Schmidt , and P\u00e5l Halvorsen . 2019 . ACM MM BioMedia 2019 Grand Challenge Overview. In: Proceedings of the ACM International Conference on Multimedia (ACM MM'19), ACM Steven Hicks, Michael Riegler, Pia Smedsrud, Trine B. Haugen, Kristin Randheim Randel, Konstantin Pogorelov, H\u00e5kon Kvale Stensland, Duc-Tien Dang-Nguyen, Mathias Lux, Andreas Petlund, Thomas de Lange, Peter Thelin Schmidt, and P\u00e5l Halvorsen. 2019. ACM MM BioMedia 2019 Grand Challenge Overview. In: Proceedings of the ACM International Conference on Multimedia (ACM MM'19), ACM"},{"key":"e_1_3_2_1_2_1","volume-title":"KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection. In: Proceedings of the 8th ACM on Multimedia Systems Conference (MMSys'17)","author":"Pogorelov Konstantin","year":"2017","unstructured":"Konstantin Pogorelov , Kristin Ranheim Randel , Carsten Griwodz , Sigrun Losada Eskeland , Thomas de Lange , Dag Johansen , Concetto Spampinato , Duc-Tien Dang-Nguyen , Mathias Lux , Peter Thelin Schmidt , Michael Riegler , and P\u00e5l Halvorsen . 2017 . KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection. In: Proceedings of the 8th ACM on Multimedia Systems Conference (MMSys'17) . ACM, 164--169. Konstantin Pogorelov, Kristin Ranheim Randel, Carsten Griwodz, Sigrun Losada Eskeland, Thomas de Lange, Dag Johansen, Concetto Spampinato, Duc-Tien Dang-Nguyen, Mathias Lux, Peter Thelin Schmidt, Michael Riegler, and P\u00e5l Halvorsen. 2017. KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection. In: Proceedings of the 8th ACM on Multimedia Systems Conference (MMSys'17). ACM, 164--169."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3083187.3083216"},{"volume-title":"IEEE Conference on Computer Vision and Pattern Recognition","author":"B.","key":"e_1_3_2_1_4_1","unstructured":"Dalal, N., Triggs, B. : Histograms of oriented gradients for human detection . In: IEEE Conference on Computer Vision and Pattern Recognition , 2005: 886--893 Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conference on Computer Vision and Pattern Recognition, 2005: 886--893"},{"volume-title":"IEEE Conference on Computer Vision and Pattern Recognition","author":"He","key":"e_1_3_2_1_5_1","unstructured":"He K, Zhang X, Ren S, Deep Residual Learning for Image Recognition[C] . In: IEEE Conference on Computer Vision and Pattern Recognition , 2016: 770--778. He K, Zhang X, Ren S, et al. Deep Residual Learning for Image Recognition[C]. In: IEEE Conference on Computer Vision and Pattern Recognition, 2016: 770--778."},{"volume-title":"IEEE Conference on Computer Vision and Pattern Recognition","author":"Wang F.","key":"e_1_3_2_1_6_1","unstructured":"F. Wang , M. Jiang , C. Qian , S. Yang , C. Li , H. Zhang , X. Wang , and X. Tang , Residual attention network for image classi?cation , In: IEEE Conference on Computer Vision and Pattern Recognition , 2017: 6450--6458 F. Wang, M. Jiang, C. Qian, S. Yang, C. Li, H. Zhang, X. Wang, and X. Tang, Residual attention network for image classi?cation, In: IEEE Conference on Computer Vision and Pattern Recognition, 2017: 6450--6458"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.5555\/2627435.2670313"},{"issue":"4","key":"e_1_3_2_1_8_1","first-page":"994","article-title":"lAutomated melanoma recognition in dermoscopy images via deep residual networks [J]","volume":"26","author":"YUL, CHENH, DOUQ","year":"2017","unstructured":"YUL, CHENH, DOUQ , e ta lAutomated melanoma recognition in dermoscopy images via deep residual networks [J] IEEE Transactions on Medical Imaging , 2017 , 26 ( 4 ): 994 -- 1004 . YUL, CHENH, DOUQ, e ta lAutomated melanoma recognition in dermoscopy images via deep residual networks [J] IEEE Transactions on Medical Imaging, 2017, 26(4):994--1004.","journal-title":"IEEE Transactions on Medical Imaging"}],"event":{"name":"MM '19: The 27th ACM International Conference on Multimedia","sponsor":["SIGMM ACM Special Interest Group on Multimedia"],"location":"Nice France","acronym":"MM '19"},"container-title":["Proceedings of the 27th ACM International Conference on Multimedia"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3343031.3356079","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3343031.3356079","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:23Z","timestamp":1750202003000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3343031.3356079"}},"subtitle":["Using Data Enhancement to Solve Sample Unbalance"],"short-title":[],"issued":{"date-parts":[[2019,10,15]]},"references-count":8,"alternative-id":["10.1145\/3343031.3356079","10.1145\/3343031"],"URL":"https:\/\/doi.org\/10.1145\/3343031.3356079","relation":{},"subject":[],"published":{"date-parts":[[2019,10,15]]},"assertion":[{"value":"2019-10-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}