{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:39:03Z","timestamp":1730302743852,"version":"3.28.0"},"reference-count":16,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,12,1]],"date-time":"2020-12-01T00:00:00Z","timestamp":1606780800000},"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":[[2020,12,1]]},"DOI":"10.1109\/vcip49819.2020.9301822","type":"proceedings-article","created":{"date-parts":[[2020,12,29]],"date-time":"2020-12-29T21:00:33Z","timestamp":1609275633000},"page":"226-229","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning Based EBCOT Source Symbol Prediction Technique for JPEG2000 Image Compression Architecture"],"prefix":"10.1109","author":[{"given":"I-Hsiang","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian-Jiun","family":"Ding","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","article-title":"An end-to-end compression framework based on convolutional neural networks","volume":"pp","author":"jiang","year":"2017","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref11","first-page":"1","article-title":"Real-time adaptive image compression","author":"rippel","year":"2017","journal-title":"Int Conf Machine Learning"},{"key":"ref12","article-title":"Improved JPEG 2000 system using LS prediction and grouping context coding scheme","author":"ding","year":"2012","journal-title":"APSIPA Annual Summit and Conference"},{"key":"ref13","first-page":"1","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2015","journal-title":"Int Conf Learning Representations"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1109\/76.499834","article-title":"A new fast and efficient image codec based on set partitioning in hierarchical trees","volume":"6","author":"said","year":"1996","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"journal-title":"The USC SIPI Image Database","year":"0","key":"ref15"},{"journal-title":"Kodak dataset","year":"0","key":"ref16"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2749449"},{"journal-title":"JPEG2000 Standard for Image Compression Concepts Algorithms and VLSI Architectures","year":"2005","author":"acharya","key":"ref3"},{"key":"ref6","first-page":"1","article-title":"Variable rate image compression with recurrent neural networks","author":"toderici","year":"2016","journal-title":"Int Conf Learning Representations"},{"journal-title":"The codes of the proposed algorithm","year":"0","key":"ref5"},{"key":"ref8","first-page":"1","article-title":"Lossy image compression with compressive autoencoders","author":"theis","year":"2017","journal-title":"Int Conf Learning Representations"},{"key":"ref7","article-title":"Improved lossy image compression with priming and spatially adaptive bit rates for recurrent networks","volume":"10","author":"johnston","year":"2017","journal-title":"Structure"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.1999.817132"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/30.920468"},{"key":"ref9","first-page":"1","article-title":"Real-time adaptive image compression","author":"rippel","year":"2017","journal-title":"Int Conf Machine Learning"}],"event":{"name":"2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)","start":{"date-parts":[[2020,12,1]]},"location":"Macau, China","end":{"date-parts":[[2020,12,4]]}},"container-title":["2020 IEEE International Conference on Visual Communications and Image Processing (VCIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9301747\/9301748\/09301822.pdf?arnumber=9301822","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T15:17:51Z","timestamp":1656602271000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9301822\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,1]]},"references-count":16,"URL":"https:\/\/doi.org\/10.1109\/vcip49819.2020.9301822","relation":{},"subject":[],"published":{"date-parts":[[2020,12,1]]}}}