{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T05:36:22Z","timestamp":1730266582300,"version":"3.28.0"},"reference-count":31,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,7]]},"DOI":"10.1109\/ijcnn.2016.7727308","type":"proceedings-article","created":{"date-parts":[[2016,11,8]],"date-time":"2016-11-08T21:15:56Z","timestamp":1478639756000},"page":"1008-1014","source":"Crossref","is-referenced-by-count":1,"title":["SAM: A rethinking of prominent convolutional neural network architectures for visual object recognition"],"prefix":"10.1109","author":[{"family":"Zhenyang Wang","sequence":"first","affiliation":[]},{"family":"Zhidong Deng","sequence":"additional","affiliation":[]},{"family":"Shiyao Wang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref31","first-page":"2094","article-title":"Discriminative transfer learning with tree-based priors","author":"srivastava","year":"2013","journal-title":"Advances in neural information processing systems"},{"key":"ref30","article-title":"Striving for simplicity: The all convolutional net","author":"springenberg","year":"2014","journal-title":"ar Xiv preprint arXiv 1412 6806"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhevsky","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref12","first-page":"5","article-title":"Reading digits in natural images with unsupervised feature learning","volume":"2011","author":"netzer","year":"2011","journal-title":"NIPS Workshop on Deep Learning and Unsupervised Feature Learning"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/0031-3203(82)90024-3"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1959.sp006308"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1113\/jphysiol.1962.sp006837"},{"key":"ref16","first-page":"21","article-title":"A theoretical framework for back-propagation","volume":"1","author":"le cun","year":"1988","journal-title":"Proc Connectionist Models Summer School"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"ref18","article-title":"Handwritten digit recognition with a backpropagation network","author":"le cun","year":"1990","journal-title":"Advances in neural information processing systems"},{"key":"ref19","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1145\/2647868.2654889"},{"key":"ref4","article-title":"Going deeper with convolutions","author":"szegedy","year":"2014","journal-title":"arXiv preprint arXiv 1409 4842"},{"key":"ref27","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"loffe","year":"2015","journal-title":"ar Xiv preprint arXiv 1502 07830"},{"key":"ref3","first-page":"886","article-title":"Histograms of oriented gradients for human detection","volume":"1","author":"dalai","year":"2005","journal-title":"Computer Vision and Pattern Recognition 2005 CVPR 2005 IEEE Computer Society Conference"},{"key":"ref6","article-title":"Maxout networks","author":"goodfellow","year":"2013","journal-title":"arXiv preprint arXiv 1302 4389"},{"key":"ref29","article-title":"Improving deep neural networks with probabilistic maxout units","author":"springenberg","year":"2013","journal-title":"ar Xiv preprint arXiv 1312 6116"},{"key":"ref5","article-title":"Rethinking the inception architecture for computer vision","author":"szegedy","year":"2015","journal-title":"arXiv preprint arXiv 1512 00327"},{"key":"ref8","article-title":"Network in network","volume":"abs 1312 4400","author":"lin","year":"2013","journal-title":"CoRR"},{"key":"ref7","article-title":"Deep residual learning for image recognition","author":"he","year":"0","journal-title":"arXiv preprint arXiv 1512 03385 2015"},{"key":"ref2","first-page":"11","article-title":"Pea-sift: A more distinctive representation for local image descriptors","volume":"2","author":"ke","year":"2004","journal-title":"Computer Vision and Pattern Recognition 2004 CVPR 2004 Proceedings of the 2004 IEEE Computer SocietyConference"},{"key":"ref9","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv preprint arXiv 1409 1556"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.1999.790410"},{"key":"ref20","article-title":"Overfeat: Integrated recognition, localization and detection using convolutional networks","author":"sermanet","year":"2013","journal-title":"arXiv preprint arXiv 1312 6229"},{"key":"ref22","article-title":"Stochastic pooling for regularization of deep convolutional neural networks","author":"zeiler","year":"2013","journal-title":"arXiv preprint arXiv 1301 3557"},{"key":"ref21","first-page":"1058","article-title":"Regu-larization of neural networks using dropconnect","author":"wan","year":"2013","journal-title":"Proceedings of the 30th International Conference on Machine Learning (ICML-13)"},{"key":"ref24","article-title":"Deeply-supervised nets","author":"lee","year":"2014","journal-title":"arXiv preprint arXiv 1409 5185"},{"key":"ref23","first-page":"3545","article-title":"Deep networks with internal selective attention through feedback connections","author":"stollenga","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref26","first-page":"2368","article-title":"Training very deep networks","author":"srivastava","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298958"}],"event":{"name":"2016 International Joint Conference on Neural Networks (IJCNN)","start":{"date-parts":[[2016,7,24]]},"location":"Vancouver, BC, Canada","end":{"date-parts":[[2016,7,29]]}},"container-title":["2016 International Joint Conference on Neural Networks (IJCNN)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7593175\/7726591\/07727308.pdf?arnumber=7727308","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2016,12,7]],"date-time":"2016-12-07T17:25:25Z","timestamp":1481131525000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/7727308\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/ijcnn.2016.7727308","relation":{},"subject":[],"published":{"date-parts":[[2016,7]]}}}