{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,18]],"date-time":"2025-11-18T12:30:29Z","timestamp":1763469029632,"version":"3.37.0"},"reference-count":45,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Soonchuhyang University Research Fund and \u201cRegional Innovation Strategy \u201d through the National Research Foundation of Korea, Ministry of Education","award":["2021RIS-004"],"award-info":[{"award-number":["2021RIS-004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3537083","type":"journal-article","created":{"date-parts":[[2025,1,30]],"date-time":"2025-01-30T19:20:36Z","timestamp":1738264836000},"page":"21734-21743","source":"Crossref","is-referenced-by-count":1,"title":["SaliencyMix+: Noise-Minimized Image Mixing Method With Saliency Map in Data Augmentation"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-8266-7448","authenticated-orcid":false,"given":"Hajeong","family":"Lee","sequence":"first","affiliation":[{"name":"Department of AI and Big Data, Soonchunhyang University, Asan-si, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1370-781X","authenticated-orcid":false,"given":"Zhixiong","family":"Jin","sequence":"additional","affiliation":[{"name":"ENTPE, LICIT-ECO7, Universit&#x00E9; Gustave Eiffel, Lyon, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8231-0018","authenticated-orcid":false,"given":"Jiyoung","family":"Woo","sequence":"additional","affiliation":[{"name":"Department of AI and Big Data, Soonchunhyang University, Asan-si, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0458-1573","authenticated-orcid":false,"given":"Byeongjoon","family":"Noh","sequence":"additional","affiliation":[{"name":"Department of AI and Big Data, Soonchunhyang University, Asan-si, Republic of Korea"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref2","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"25","author":"Krizhevsky"},{"key":"ref3","first-page":"91","article-title":"Faster R-CNN: Towards real-time object detection with region proposal networks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"28","author":"Ren"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref6","article-title":"Semantic image segmentation with deep convolutional nets and fully connected CRFs","author":"Chen","year":"2014","journal-title":"arXiv:1412.7062"},{"key":"ref7","article-title":"Improved regularization of convolutional neural networks with cutout","author":"DeVries","year":"2017","journal-title":"arXiv:1708.04552"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00612"},{"key":"ref9","article-title":"SaliencyMix: A saliency guided data augmentation strategy for better regularization","author":"Uddin","year":"2020","journal-title":"arXiv:2006.01791"},{"key":"ref10","first-page":"1","article-title":"Mixup: Beyond empirical risk minimization","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zhang"},{"key":"ref11","first-page":"6438","article-title":"Manifold mixup: Better representations by interpolating hidden states","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Verma"},{"key":"ref12","first-page":"6665","article-title":"Fast AutoAugment","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Lim"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW50498.2020.00359"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00081"},{"key":"ref15","first-page":"2797","article-title":"A Bayesian data augmentation approach for learning deep models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Tran"},{"key":"ref16","article-title":"AugMix: A simple data processing method to improve robustness and uncertainty","author":"Hendrycks","year":"2019","journal-title":"arXiv:1912.02781"},{"key":"ref17","first-page":"5275","article-title":"Puzzle mix: Exploiting saliency and local statistics for optimal mixup","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kim"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/s11760-023-02852-0"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-021-00815-1"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11223795"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.health.2024.100340"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00020"},{"key":"ref23","article-title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","author":"Simonyan","year":"2013","journal-title":"arXiv:1312.6034"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248093"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.80"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00154"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_14"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2966647"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2018.2870832"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-08849-y"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref32","first-page":"3319","article-title":"Axiomatic attribution for deep networks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Sundararajan"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00097"},{"key":"ref34","article-title":"Smooth Grad-CAM++: An enhanced inference level visualization technique for deep convolutional neural network models","author":"Omeiza","year":"2019","journal-title":"arXiv:1908.01224"},{"key":"ref35","article-title":"Expected grad-CAM: Towards gradient faithfulness","author":"Buono","year":"2024","journal-title":"arXiv:2406.01274"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00288"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09875-6"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2021.3071691"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-021-02759-8"},{"key":"ref40","article-title":"On the connection between adversarial robustness and saliency map interpretability","author":"Etmann","year":"2019","journal-title":"arXiv:1905.04172"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2019.01.010"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120858"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2024.3397697"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10858701.pdf?arnumber=10858701","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T05:39:55Z","timestamp":1738820395000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10858701\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":45,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3537083","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2025]]}}}