{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,7]],"date-time":"2024-09-07T19:55:37Z","timestamp":1725738937843},"reference-count":29,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,5,23]],"date-time":"2022-05-23T00:00:00Z","timestamp":1653264000000},"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":[[2022,5,23]]},"DOI":"10.1109\/icassp43922.2022.9746695","type":"proceedings-article","created":{"date-parts":[[2022,4,27]],"date-time":"2022-04-27T19:50:34Z","timestamp":1651089034000},"page":"2415-2419","source":"Crossref","is-referenced-by-count":4,"title":["SDNET: Lightweight Facial Expression Recognition For Sample Disequilibrium"],"prefix":"10.1109","author":[{"given":"Lifang","family":"Zhou","sequence":"first","affiliation":[{"name":"Chongqing University of Posts and Telecommunications,College of Computer Science and Technology,Chongqing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siqin","family":"Li","sequence":"additional","affiliation":[{"name":"Chongqing University of Posts and Telecommunications,College of Computer Science and Technology,Chongqing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Wang","sequence":"additional","affiliation":[{"name":"Chongqing University of Posts and Telecommunications,College of Software,Chongqing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junlin","family":"Liu","sequence":"additional","affiliation":[{"name":"Chongqing University of Posts and Telecommunications,College of Software,Chongqing,China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803654"},{"key":"ref11","first-page":"19","article-title":"Local binary convolutional neural networks","author":"xu","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref12","first-page":"1251","article-title":"Xception: Deep learning with depthwise separable convolutions","author":"fran\u00e7ois","year":"2017","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00140"},{"key":"ref14","first-page":"116","article-title":"Shufflenet v2: Practical guidelines for efficient cnn architecture design","author":"ma","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00165"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5543262"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.imavis.2011.07.002"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00051"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/IPTA.2019.8936114"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/3240508.3240574"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-42051-1_16"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2962317"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1002\/tee.22151"},{"article-title":"Mobilenets: Efficient convolutional neural networks for mobile vision applications","year":"2017","author":"howard","key":"ref6"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.03.034"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2011.6130508"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.3390\/s20092639"},{"article-title":"Squeezenet: Alexnet-level accuracy with 50x fewer parameters and¡ 0.5 mb model size","year":"2016","author":"iandola","key":"ref7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2019.01.002"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.04.041"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2018.2829707"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01400"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413822"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01261-8_14"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.03.019"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1131-1"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.07.028"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00286"}],"event":{"name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","start":{"date-parts":[[2022,5,23]]},"location":"Singapore, Singapore","end":{"date-parts":[[2022,5,27]]}},"container-title":["ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9745891\/9746004\/09746695.pdf?arnumber=9746695","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,15]],"date-time":"2022-08-15T20:07:08Z","timestamp":1660594028000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9746695\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,23]]},"references-count":29,"URL":"https:\/\/doi.org\/10.1109\/icassp43922.2022.9746695","relation":{},"subject":[],"published":{"date-parts":[[2022,5,23]]}}}