{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T21:21:32Z","timestamp":1768512092009,"version":"3.49.0"},"reference-count":50,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/access.2022.3159911","type":"journal-article","created":{"date-parts":[[2022,3,16]],"date-time":"2022-03-16T19:38:47Z","timestamp":1647459527000},"page":"36327-36334","source":"Crossref","is-referenced-by-count":9,"title":["Bayesian Neural Networks for Reversible Steganography"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7723-4591","authenticated-orcid":false,"given":"Ching-Chun","family":"Chang","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Warwick, Coventry, U.K."}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1093\/mind\/LIX.236.433"},{"key":"ref2","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst. (NeurIPS)","author":"Krizhevsky"},{"key":"ref3","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Simonyan"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3134599"},{"key":"ref6","first-page":"1","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Goodfellow"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140451"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3427228.3427268"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/359340.359342"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/BF00196791"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/49.668971"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1117\/12.435400"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2003.815962"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2003.809729"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2006.869964"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2007.905146"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2016.2573308"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2891247"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/4932782"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01067"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1948.tb01338.x"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3034936"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2021.3059202"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5580272"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2017\/661"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3409383"},{"key":"ref27","article-title":"Uncertainty in deep learning","author":"Gal","year":"2016"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2004.840686"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.891046"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2009.2020257"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2150233"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2014.2307482"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1923.10502116"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-45528-0"},{"key":"ref35","volume-title":"Machine Learning: A Probabilistic Perspective","author":"Murphy","year":"2012"},{"key":"ref36","volume-title":"Deep Learning","author":"Goodfellow","year":"2016"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1017\/9781108679930"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1145\/168304.168306"},{"issue":"2","key":"ref39","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1023\/A:1007665907178","article-title":"An introduction to variational methods for graphical models","volume":"37","author":"Jordan","year":"1999","journal-title":"Mach. Learn."},{"key":"ref40","first-page":"1","article-title":"Auto-encoding variational Bayes","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Kingma"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.5555\/2986459.2986721"},{"key":"ref42","first-page":"1613","article-title":"Weight uncertainty in neural networks","volume-title":"Proc. Int. Conf. Mach. Learn. (ICML)","author":"Blundell"},{"key":"ref43","first-page":"1","article-title":"Bayesian convolutional neural networks with Bernoulli approximate variational inference","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Gal"},{"issue":"1","key":"ref44","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.5555\/3045390.3045502"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.5555\/3295222.3295309"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1994.374138"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00262"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-24178-9_5"},{"key":"ref50","article-title":"The USC-SIPI image database: Version 5","author":"Weber","year":"2006"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9668973\/09736990.pdf?arnumber=9736990","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,18]],"date-time":"2024-01-18T00:02:16Z","timestamp":1705536136000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9736990\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":50,"URL":"https:\/\/doi.org\/10.1109\/access.2022.3159911","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]}}}