{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:00:36Z","timestamp":1740132036861,"version":"3.37.3"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"3","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["1717775"],"award-info":[{"award-number":["1717775"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst."],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1109\/tcad.2021.3061520","type":"journal-article","created":{"date-parts":[[2021,2,23]],"date-time":"2021-02-23T21:04:12Z","timestamp":1614114252000},"page":"530-543","source":"Crossref","is-referenced-by-count":2,"title":["CaptorX: A Class-Adaptive Convolutional Neural Network Reconfiguration Framework"],"prefix":"10.1109","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5465-7740","authenticated-orcid":false,"given":"Zhuwei","family":"Qin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4880-6658","authenticated-orcid":false,"given":"Fuxun","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3556-9358","authenticated-orcid":false,"given":"Zirui","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7749-0640","authenticated-orcid":false,"given":"Chenchen","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2790-976X","authenticated-orcid":false,"given":"Xiang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"volume-title":"MobileNets: Efficient convolutional neural networks for mobile vision applications","year":"2017","author":"Howard","key":"ref2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2020.3033498"},{"volume-title":"Monotag\u2014Image Recognition!\u201d Download Best Mobile Apps in AppCrawlr","year":"2018","key":"ref4"},{"volume-title":"Once-for-all: Train one network and specialize it for efficient deployment","year":"2019","author":"Cai","key":"ref5"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2020.2995813"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3287624.3287643"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.58"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3293353.3293383"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.354"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967280"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3218603.3218652"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.643"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.7731\/table-1"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.5555\/2999134.2999257"},{"volume-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"Simonyan","key":"ref16"},{"article-title":"Network in network","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Lin","key":"ref17"},{"key":"ref18","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume-title":"Proc. Neural Inf. Process. Syst.","author":"Han"},{"article-title":"Pruning filters for efficient convnets","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Li","key":"ref19"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.155"},{"key":"ref21","first-page":"92","article-title":"Functionality-oriented convolutional filter pruning","volume-title":"Proc. Brit. Mach. Vis. Conf.","author":"Qin"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.23919\/DATE48585.2020.9116429"},{"article-title":"Demystifying neural network filter pruning","volume-title":"Proc. Workshop Compact Deep Neural Netw. Ind. Appl.","author":"Qin","key":"ref23"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.5244\/C.28.88"},{"volume-title":"Binarized neural networks: Training deep neural networks with weights and activations constrained to +1 or \u22121","year":"2016","author":"Courbariaux","key":"ref25"},{"key":"ref26","first-page":"598","article-title":"Optimal brain damage","volume-title":"Proc. Neural Inf. Process. Syst. (NIPS)","author":"LeCun"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ICNN.1993.298572"},{"article-title":"Pruning convolutional neural networks for resource efficient inference","volume-title":"Proc. Int. Conf. Learn. Represent. (ICLR)","author":"Molchanov","key":"ref28"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.3934\/mfc.2018008"},{"volume-title":"Object detectors emerge in deep scene CNNs","year":"2014","author":"Zhou","key":"ref30"},{"article-title":"Understanding neural networks through deep visualization","volume-title":"Proc. Int. Conf. Mach. Learn. Workshops","author":"Yosinski","key":"ref31"},{"article-title":"Visualizing higher-layer features of a deep network","year":"2009","author":"Erhan","key":"ref32"},{"volume-title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","year":"2013","author":"Simonyan","key":"ref33"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.5555\/2685048.2685095"},{"volume-title":"Heterogeneous federated learning","year":"2020","author":"Yu","key":"ref35"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203791"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref37"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.09.010"}],"container-title":["IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/43\/9716240\/09360865.pdf?arnumber=9360865","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T23:57:53Z","timestamp":1704844673000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9360865\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3]]},"references-count":38,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.1109\/tcad.2021.3061520","relation":{},"ISSN":["0278-0070","1937-4151"],"issn-type":[{"type":"print","value":"0278-0070"},{"type":"electronic","value":"1937-4151"}],"subject":[],"published":{"date-parts":[[2022,3]]}}}