{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T13:46:32Z","timestamp":1730209592443,"version":"3.28.0"},"reference-count":28,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,5,14]],"date-time":"2021-05-14T00:00:00Z","timestamp":1620950400000},"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":[[2021,5,14]]},"DOI":"10.1109\/cogsima51574.2021.9475948","type":"proceedings-article","created":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T16:13:37Z","timestamp":1625847217000},"page":"66-72","source":"Crossref","is-referenced-by-count":1,"title":["Expression recognition based on multiple feature fusion-based convolutional neural network"],"prefix":"10.1109","author":[{"given":"Danqing","family":"Qian","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liulei","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiming","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cheng","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.2964298"},{"key":"ref11","first-page":"2377","article-title":"Training very deep networks","author":"srivastava","year":"2015","journal-title":"Neural Information Processing Systems 2015"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref13","first-page":"1","article-title":"Fractalnet: ultra-deep neural networks without residuals","author":"larsson","year":"2017","journal-title":"5th International Conference on Learning Representations"},{"key":"ref14","first-page":"1930","article-title":"A Segmentation Method of Ultrasonic Image Left Ventricle Based on Convolutional Neural Network","volume":"39","author":"wu","year":"2019","journal-title":"Chinese Journal of Image and Graphics"},{"key":"ref15","first-page":"176","article-title":"Facial expression recognition based on cross-connected LeNet-5 network","author":"li","year":"2018","journal-title":"ACTA Automatica Sinica"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CCWC47524.2020.9031283"},{"key":"ref17","first-page":"448","article-title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","author":"ioffe","year":"2015","journal-title":"32nd International Conference on Machine Learning"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2010.5543262"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2006.884954"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/SERA.2017.7965717"},{"article-title":"Real-time Convolutional Neural Networks for Emotion and Gender Classification","year":"2017","author":"arriaga","key":"ref28"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/IDAP.2017.8090281"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2018.00068"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref5","first-page":"1097","article-title":"ImageNet Classification with Deep Convolutional Neural Networks","author":"krizhevsky","year":"2012","journal-title":"Neural Information Processing Systems"},{"key":"ref8","first-page":"364","article-title":"Convolution Neural Network with Multi-Resolution Feature Fusion for Facial Expression Recognition","volume":"55","author":"he","year":"2018","journal-title":"Laser & Optoelectronics Progress"},{"key":"ref7","first-page":"2969","article-title":"Facial expression recognition based on cross-connection feature fusion network","volume":"10","author":"huang","year":"2019","journal-title":"Smart Computing and Informatics"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/DASC-PICom-DataCom-CyberSciTec.2017.213"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICIEA.2019.8834383"},{"key":"ref1","article-title":"Research on Facial Expression Recognition Based on Convolutional Neural Network","volume":"14","author":"fang","year":"2019","journal-title":"Modern information technology"},{"key":"ref20","first-page":"1","article-title":"Facial expression recognition based on improved AlexNet","author":"yang","year":"2020","journal-title":"Laser &amp; Optoelectronics Progress"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1049\/cp.2015.1766"},{"key":"ref21","first-page":"227","article-title":"Constructing a parallel convolutional neural network expression recognition algorithm","author":"xu","year":"2019","journal-title":"Chinese Journal of Image and Graphics"},{"key":"ref24","first-page":"745","article-title":"Facial expression recognition through deep learning","author":"fathallah","year":"2017","journal-title":"2017 IEEE\/ACS 14th International Conference on Computer Systems and Applications"},{"key":"ref23","first-page":"2509","article-title":"Facial expression recognition based on LBP\/VAR and DBN model","volume":"8","author":"he","year":"2016","journal-title":"Application Research of Computers"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2016.7477450"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1109\/CW.2016.34","article-title":"Facial Expression Recognition with CNN Ensemble","author":"liu","year":"2016","journal-title":"2016 International Conference on Cyberworlds"}],"event":{"name":"2021 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)","start":{"date-parts":[[2021,5,14]]},"location":"Tallinn, Estonia","end":{"date-parts":[[2021,5,22]]}},"container-title":["2021 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9475901\/9475917\/09475948.pdf?arnumber=9475948","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T11:43:13Z","timestamp":1652182993000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9475948\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,14]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/cogsima51574.2021.9475948","relation":{},"subject":[],"published":{"date-parts":[[2021,5,14]]}}}