{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T00:16:41Z","timestamp":1780359401783,"version":"3.54.1"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,9,1]],"date-time":"2022-09-01T00:00:00Z","timestamp":1661990400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2020YFB1707601"],"award-info":[{"award-number":["2020YFB1707601"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Ind. Inf."],"published-print":{"date-parts":[[2022,9]]},"DOI":"10.1109\/tii.2022.3154473","type":"journal-article","created":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T20:33:48Z","timestamp":1645821228000},"page":"6300-6307","source":"Crossref","is-referenced-by-count":34,"title":["CroApp: A CNN-Based Resource Optimization Approach in Edge Computing Environment"],"prefix":"10.1109","volume":"18","author":[{"given":"Yongzhe","family":"Jia","sequence":"first","affiliation":[{"name":"Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5949-9756","authenticated-orcid":false,"given":"Bowen","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4833-2023","authenticated-orcid":false,"given":"Wanchun","family":"Dou","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4879-9803","authenticated-orcid":false,"given":"Xiaolong","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer and Software, Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3488-4679","authenticated-orcid":false,"given":"Xiaokang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Faculty of Data Science, Shiga University, Hikone, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7746-4901","authenticated-orcid":false,"given":"Lianyong","family":"Qi","sequence":"additional","affiliation":[{"name":"School of Computer Science, Qufu Normal University, Rizhao, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9697-2108","authenticated-orcid":false,"given":"Zheng","family":"Yan","sequence":"additional","affiliation":[{"name":"State Key Laboratory on Integrated Services Networks and the School of Cyber Engineering, Xidian University, Xi’an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref30","first-page":"8137","article-title":"Split-and-bridge: Adaptable class incremental learning within a single neural network","author":"kim","year":"0","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01403"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.23919\/DATE48585.2020.9116350"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/SEC.2018.00016"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3020583"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3044930"},{"key":"ref15","first-page":"10717","article-title":"Accelerate CNNs from three dimensions: A comprehensive pruning framework","author":"wang","year":"0","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref16","article-title":"CHIP: Channel independence-based pruning for compact neural networks","author":"sui","year":"0","journal-title":"Proc Int Conf Neural Inf Process"},{"key":"ref17","first-page":"29","article-title":"Mainstream: Dynamic stem-sharing for multi-tenant video processing","author":"jiang","year":"0","journal-title":"Proc USENIX Annu Tech Conf"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP40776.2020.9053918"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2021.3129615"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3073066"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2020.2996231"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3077937"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2904897"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2020.09.016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCBB.2020.2994780"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2021.3119950"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3116085"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2020.2970550"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3047675"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2016.2579198"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107636"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.acl-long.378"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00650"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_1"},{"key":"ref23","article-title":"Spatial group-wise enhance: Improving semantic feature learning in convolutional networks","author":"li","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/2906388.2906396"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"}],"container-title":["IEEE Transactions on Industrial Informatics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9424\/9795344\/09721644.pdf?arnumber=9721644","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,25]],"date-time":"2022-07-25T19:53:32Z","timestamp":1658778812000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9721644\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9]]},"references-count":30,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tii.2022.3154473","relation":{},"ISSN":["1551-3203","1941-0050"],"issn-type":[{"value":"1551-3203","type":"print"},{"value":"1941-0050","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9]]}}}