{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T18:33:59Z","timestamp":1769538839851,"version":"3.49.0"},"reference-count":23,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,7,1]],"date-time":"2019-07-01T00:00:00Z","timestamp":1561939200000},"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":[[2019,7]]},"DOI":"10.1109\/ijcnn.2019.8852439","type":"proceedings-article","created":{"date-parts":[[2019,9,30]],"date-time":"2019-09-30T23:44:32Z","timestamp":1569887072000},"page":"1-8","source":"Crossref","is-referenced-by-count":4,"title":["Training a V1 Like Layer Using Gabor Filters in Convolutional Neural Networks"],"prefix":"10.1109","author":[{"given":"Jun","family":"Bai","sequence":"first","affiliation":[{"name":"Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]},{"given":"Yi","family":"Zeng","sequence":"additional","affiliation":[{"name":"Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]},{"given":"Yuxuan","family":"Zhao","sequence":"additional","affiliation":[{"name":"Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]},{"given":"Feifei","family":"Zhao","sequence":"additional","affiliation":[{"name":"Research Center for Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(03)00115-1"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1968.sp008455"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1364\/JOSA.70.001297"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1152\/jn.1987.58.6.1233"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1016\/0042-6989(80)90065-6"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2012.272"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2835143"},{"key":"ref17","first-page":"386","article-title":"Gabor feature based convolutional neural network for object recognition in natural scene","author":"hu","year":"0"},{"key":"ref18","article-title":"Gabor filter assisted energy efficient fast learning convolutional neural networks","author":"shakib sarwar","year":"2017"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1959.sp006308"},{"key":"ref4","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"International Conference on Neural Information Processing Systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref6","article-title":"A sensitivity analysis of (and practitioners’ guide to) convolutional neural networks for sentence classification","volume":"10","author":"zhang","year":"2015"},{"key":"ref5","first-page":"4277","article-title":"Applying convolutional neural networks concepts to hybrid nn-hmm model for speech recognition","author":"abdel-hamid","year":"2012","journal-title":"IEEE International Conference on Acoustics Speech and Signal Processing"},{"key":"ref8","article-title":"Very deep convolutional networks for large-scale image recognition","volume":"9","author":"simonyan","year":"2014"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1181"},{"key":"ref2","author":"schmidhuber","year":"2015","journal-title":"Neural Networks and Deep Learning"},{"key":"ref1","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref9","article-title":"Going deeper with convolutions","volume":"9","author":"szegedy","year":"2014"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/BF00204594"},{"key":"ref22","first-page":"315","article-title":"Deep sparse rectifier neural networks","author":"glorot","year":"2012","journal-title":"International Conference on Artificial Intelligence and Statistics"},{"key":"ref21","first-page":"807","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"International Conference on International Conference on Machine Learning"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2807412"}],"event":{"name":"2019 International Joint Conference on Neural Networks (IJCNN)","location":"Budapest, Hungary","start":{"date-parts":[[2019,7,14]]},"end":{"date-parts":[[2019,7,19]]}},"container-title":["2019 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8840768\/8851681\/08852439.pdf?arnumber=8852439","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T05:27:04Z","timestamp":1769491624000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8852439\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2019.8852439","relation":{},"subject":[],"published":{"date-parts":[[2019,7]]}}}