{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T11:13:07Z","timestamp":1730200387365,"version":"3.28.0"},"reference-count":16,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,12]]},"DOI":"10.1109\/bigdata.2018.8622437","type":"proceedings-article","created":{"date-parts":[[2019,1,25]],"date-time":"2019-01-25T03:07:18Z","timestamp":1548385638000},"page":"2280-2287","source":"Crossref","is-referenced-by-count":13,"title":["Transfer Learning Effects on Image Steganalysis with Pre-Trained Deep Residual Neural Network Model"],"prefix":"10.1109","author":[{"given":"Selim","family":"Ozcan","sequence":"first","affiliation":[]},{"given":"Ahmet Fatih","family":"Mustacoglu","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Deep Convolutional Neural Network to Detect J-UNIWARD","year":"0","author":"xu","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2016.2548421"},{"article-title":"JPEG Steganalysis Based on DenseNet","year":"2017","author":"yang","key":"ref12"},{"article-title":"A Novel Convolutional Neural Network for Image Steganalysis with Shared Normalization","year":"2017","author":"wu","key":"ref13"},{"key":"ref14","first-page":"14","article-title":"Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover source-mismatch","author":"pibre","year":"2015"},{"key":"ref15","first-page":"1233","article-title":"Steganalysis via deep residual network","author":"wu","year":"2017","journal-title":"ICPADS '97 Proceedings of International Conference on Parallel and Distributed Systems"},{"key":"ref16","article-title":"Deep residual learning for image steganalysis","author":"wu","year":"2017","journal-title":"Multimedia Tools and Applications"},{"journal-title":"Feature learning for steganalysis using convolutional neural networks","year":"0","author":"qian","key":"ref4"},{"article-title":"Deep learning for steganalysis via convolutional neural networks","year":"2015","author":"qian","key":"ref3"},{"key":"ref6","article-title":"Convolutional neural network steganalysis&#x2019;s application to steganography","author":"sharifzadeh","year":"2018","journal-title":"2017 IEEE Visual Communications and Image Processing"},{"article-title":"Steganalysis via a Convolutional Neural Network using Large Convolution Filters for Embedding Process with Same Stego Key","year":"2016","author":"couchot","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2710946"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/IWSSIP.2017.7965617"},{"journal-title":"Learning and Transferring Representations For Image Steganalysis Using Convolutional Neural Network","year":"0","author":"qian","key":"ref2"},{"key":"ref1","first-page":"51","article-title":"An Overview of Image Steganography","volume":"83","author":"morkel","year":"2005","journal-title":"Inf Comput Secur Archit Res Gr"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2017.8019304"}],"event":{"name":"2018 IEEE International Conference on Big Data (Big Data)","start":{"date-parts":[[2018,12,10]]},"location":"Seattle, WA, USA","end":{"date-parts":[[2018,12,13]]}},"container-title":["2018 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8610059\/8621858\/08622437.pdf?arnumber=8622437","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T23:35:48Z","timestamp":1643240148000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8622437\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,12]]},"references-count":16,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2018.8622437","relation":{},"subject":[],"published":{"date-parts":[[2018,12]]}}}