{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:20:04Z","timestamp":1750220404526,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":22,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,9,21]],"date-time":"2021-09-21T00:00:00Z","timestamp":1632182400000},"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":[[2021,9,21]]},"DOI":"10.1145\/3460418.3479375","type":"proceedings-article","created":{"date-parts":[[2021,9,24]],"date-time":"2021-09-24T17:56:41Z","timestamp":1632506201000},"page":"401-407","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Triple-O for SHL Recognition Challenge: An Ensemble Framework for Multi-class Imbalance and Training-testing Distribution Inconsistency by OvO Binarization with Confidence Weight of One-class Classification"],"prefix":"10.1145","author":[{"given":"Jinhua","family":"Su","sequence":"first","affiliation":[{"name":"Renmin University of China, China"}]},{"given":"Yuanyuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Baixingkefu Network Technology Co., Ltd., China"}]}],"member":"320","published-online":{"date-parts":[[2021,9,24]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Proceedings of the european symposium on artificial neural networks, computational intelligence and machine learning. 385\u2013390","author":"Adnan Md\u00a0Nasim","year":"2015","unstructured":"Md\u00a0Nasim Adnan and Md\u00a0Zahidul Islam . 2015 . One-vs-all binarization technique in the context of random forest . In Proceedings of the european symposium on artificial neural networks, computational intelligence and machine learning. 385\u2013390 . Md\u00a0Nasim Adnan and Md\u00a0Zahidul Islam. 2015. One-vs-all binarization technique in the context of random forest. In Proceedings of the european symposium on artificial neural networks, computational intelligence and machine learning. 385\u2013390."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2917920"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2011.01.017"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2858933"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/11538059_91"},{"key":"e_1_3_2_1_6_1","volume-title":"Multi-class learning by smoothed boosting. Machine learning 67, 3","author":"Jin Rong","year":"2007","unstructured":"Rong Jin and Jian Zhang . 2007. Multi-class learning by smoothed boosting. Machine learning 67, 3 ( 2007 ), 207\u2013227. Rong Jin and Jian Zhang. 2007. Multi-class learning by smoothed boosting. Machine learning 67, 3 (2007), 207\u2013227."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-59650-1_3"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5907"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034448"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00877"},{"key":"e_1_3_2_1_11_1","unstructured":"Rajeev Ranjan Carlos\u00a0D Castillo and Rama Chellappa. 2017. L2-constrained softmax loss for discriminative face verification. arXiv preprint arXiv:1703.09507(2017).  Rajeev Ranjan Carlos\u00a0D Castillo and Rama Chellappa. 2017. L2-constrained softmax loss for discriminative face verification. arXiv preprint arXiv:1703.09507(2017)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/368"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2007.04.009"},{"key":"e_1_3_2_1_14_1","unstructured":"David Martinus\u00a0Johannes Tax. 2002. One-class classification: Concept learning in the absence of counter-examples.(2002).  David Martinus\u00a0Johannes Tax. 2002. One-class classification: Concept learning in the absence of counter-examples.(2002)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00552"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341162.3344872"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3410530.3414341"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460418.3479373"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2890793"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3267305.3267519"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-01142-4"},{"key":"e_1_3_2_1_22_1","volume-title":"2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2387\u20132390","author":"Wu Wei","year":"2006","unstructured":"Wei Wu , Xiaorong Gao , and Shangkai Gao . 2006 . One-versus-the-rest (OVR) algorithm: An extension of common spatial patterns (CSP) algorithm to multi-class case . In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2387\u20132390 . Wei Wu, Xiaorong Gao, and Shangkai Gao. 2006. One-versus-the-rest (OVR) algorithm: An extension of common spatial patterns (CSP) algorithm to multi-class case. In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2387\u20132390."}],"event":{"name":"UbiComp '21: The 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing","sponsor":["SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGSPATIAL ACM Special Interest Group on Spatial Information"],"location":"Virtual USA","acronym":"UbiComp '21"},"container-title":["Adjunct Proceedings of the 2021 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2021 ACM International Symposium on Wearable Computers"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460418.3479375","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3460418.3479375","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:56Z","timestamp":1750191536000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3460418.3479375"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,9,21]]},"references-count":22,"alternative-id":["10.1145\/3460418.3479375","10.1145\/3460418"],"URL":"https:\/\/doi.org\/10.1145\/3460418.3479375","relation":{},"subject":[],"published":{"date-parts":[[2021,9,21]]},"assertion":[{"value":"2021-09-24","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}