{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:33:31Z","timestamp":1763192011150,"version":"3.45.0"},"reference-count":33,"publisher":"IEEE","license":[{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T00:00:00Z","timestamp":1751241600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,6,30]]},"DOI":"10.1109\/ijcnn64981.2025.11229283","type":"proceedings-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T18:46:15Z","timestamp":1763145975000},"page":"1-8","source":"Crossref","is-referenced-by-count":0,"title":["Mitigating Long-Tailed Anomaly Score Distributions with Importance-Weighted Loss"],"prefix":"10.1109","author":[{"given":"Jungi","family":"Lee","sequence":"first","affiliation":[{"name":"ELROILAB Inc.,R&D Division,Seoul,Republic of Korea"}]},{"given":"Jungkwon","family":"Kim","sequence":"additional","affiliation":[{"name":"ELROILAB Inc.,R&D Division,Seoul,Republic of Korea"}]},{"given":"Chi","family":"Zhang","sequence":"additional","affiliation":[{"name":"ELROILAB Inc.,R&D Division,Seoul,Republic of Korea"}]},{"given":"Sangmin","family":"Kim","sequence":"additional","affiliation":[{"name":"ELROILAB Inc.,R&D Division,Seoul,Republic of Korea"}]},{"given":"Kwangsun","family":"Yoo","sequence":"additional","affiliation":[{"name":"ELROILAB Inc.,R&D Division,Seoul,Republic of Korea"}]},{"given":"Seok-Joo","family":"Byun","sequence":"additional","affiliation":[{"name":"ELROILAB Inc.,R&D Division,Seoul,Republic of Korea"}]}],"member":"263","reference":[{"article-title":"Anomaly detection with hyperspectral imaging for food safety inspection","year":"2024","author":"Lee","key":"ref1"},{"key":"ref2","article-title":"Stochastic neighbor embedding","volume":"15","author":"Hinton","year":"2002","journal-title":"Advances in neural information processing systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3268118"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TSMCB.2008.2007853"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1613\/jair.953"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00076"},{"key":"ref7","article-title":"mixup: Beyond empirical risk minimization","volume-title":"International Conference on Learning Representations","author":"Zhang","year":"2018"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01622"},{"key":"ref9","first-page":"19 290","article-title":"Rethinking the value of labels for improving class-imbalanced learning","volume":"33","author":"Yang","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-65414-6_11"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1111\/j.0824-7935.2004.t01-1-00228.x"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.5555\/1642194.1642224"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2006.17"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2007.04.009"},{"key":"ref15","article-title":"Learning to model the tail","volume":"30","author":"Wang","year":"2017","journal-title":"Advances in neural information processing systems"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00378"},{"key":"ref17","article-title":"Decoupling representation and classifier for long-tailed recognition","volume-title":"International Conference on Learning Representations","author":"Kang","year":"2020"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330896"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01182"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611972740.22"},{"key":"ref21","article-title":"Mnist handwritten digit database","volume-title":"ATT Labs","volume":"2","author":"LeCun","year":"2010"},{"key":"ref22","article-title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms","volume-title":"CoRR","author":"Xiao","year":"2017"},{"key":"ref23","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009","journal-title":"Tech. Rep."},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00179"},{"key":"ref25","first-page":"4393","article-title":"Deep one-class classification","volume-title":"International conference on machine learning","author":"Ruff"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.5220\/0007364500002108"},{"key":"ref28","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","volume-title":"International conference on machine learning","author":"Ioffe"},{"article-title":"Empirical evaluation of rectified activations in convolutional network","year":"2015","author":"Xu","key":"ref29"},{"article-title":"Adam: A method for stochastic optimization","year":"2014","author":"Kingma","key":"ref30"},{"key":"ref31","article-title":"Rapp: Novelty detection with reconstruction along projection pathway","volume-title":"International Conference on Learning Representations","author":"Kim","year":"2020"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2023.3270293"},{"key":"ref33","first-page":"38 655","article-title":"Fascinating supervisory signals and where to find them: Deep anomaly detection with scale learning","volume-title":"International Conference on Machine Learning","author":"Xu"}],"event":{"name":"2025 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2025,6,30]]},"location":"Rome, Italy","end":{"date-parts":[[2025,7,5]]}},"container-title":["2025 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/11227166\/11227148\/11229283.pdf?arnumber=11229283","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T07:30:25Z","timestamp":1763191825000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11229283\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,30]]},"references-count":33,"URL":"https:\/\/doi.org\/10.1109\/ijcnn64981.2025.11229283","relation":{},"subject":[],"published":{"date-parts":[[2025,6,30]]}}}