{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,30]],"date-time":"2025-06-30T04:04:20Z","timestamp":1751256260846,"version":"3.41.0"},"reference-count":38,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,11]]},"DOI":"10.1109\/icsai.2017.8248500","type":"proceedings-article","created":{"date-parts":[[2018,1,8]],"date-time":"2018-01-08T22:42:24Z","timestamp":1515451344000},"page":"1373-1377","source":"Crossref","is-referenced-by-count":1,"title":["Difference networks and second-order difference networks"],"prefix":"10.1109","author":[{"given":"Changxing","family":"Jing","sequence":"first","affiliation":[]},{"given":"Dongping","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Peiqing","family":"Ni","sequence":"additional","affiliation":[]},{"given":"Kun","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Li","family":"Yang","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"ref33","first-page":"1026","author":"he","year":"2015","journal-title":"Delving deep into rectifiers Surpassing human-level performance on imagenet classification[C]\/\/Proceedings of the IEEE international conference on computer vision"},{"key":"ref32","first-page":"189","author":"learned-miller","year":"2016","journal-title":"Labeled faces in the wild A survey[M]\/\/Advances in face detection and facial image analysis"},{"journal-title":"Deep residual networks with exponential linear unit","year":"2016","author":"shah","key":"ref31"},{"journal-title":"Resnet in resnet Generalizing residual architectures","year":"2016","author":"targ","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2017.2654543"},{"key":"ref36","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref35","article-title":"Densely Connected Convolutional Networks[J]","author":"huang","year":"2016","journal-title":"Computer Vision and Pattern Recognition arXiv"},{"journal-title":"Learning face representation from scratch[J]","year":"2014","author":"yi","key":"ref34"},{"journal-title":"Striving for simplicity The all convolutional net","year":"2014","author":"springenberg","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"journal-title":"Deep residual learning for image recognition","year":"2015","author":"he","key":"ref12"},{"journal-title":"Identity mappings in deep residual networks","year":"2016","author":"he","key":"ref13"},{"journal-title":"Wide residual networks","year":"2016","author":"zagoruyko","key":"ref14"},{"journal-title":"Deep networks with stochastic depth","year":"2016","author":"huang","key":"ref15"},{"journal-title":"Learning multiple layers of features from tiny images","year":"2009","author":"krizhenvshky","key":"ref16"},{"key":"ref17","first-page":"675","author":"jia","year":"2014","journal-title":"Caffe Convolutional architecture for fast feature embedding[C]\/\/Proceedings of the 22nd ACM international conference on Multimedia ACM"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/72.279181"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"journal-title":"Highway networks","year":"2015","author":"srivastava","key":"ref28"},{"journal-title":"Empirical evaluation of rectified activations in convolutional network","year":"2015","author":"xu","key":"ref4"},{"journal-title":"Maxout Networks","year":"2013","author":"goodfellow","key":"ref27"},{"journal-title":"Generic object detection with dense neural patterns and regionlets","year":"2014","author":"zou","key":"ref3"},{"journal-title":"Overfeat Integrated Recognition Localization and Detection Using Convolutional Networks","year":"2013","author":"sermanet","key":"ref6"},{"key":"ref29","first-page":"499","author":"wen","year":"2016","journal-title":"A discriminative feature learning approach for deep face recognition[C]\/\/European Conference on Computer Vision"},{"journal-title":"Network in Network","year":"2013","author":"lin","key":"ref5"},{"journal-title":"Fitnets Hints for thin deep nets","year":"2014","author":"romero","key":"ref8"},{"journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition","year":"2014","author":"simonyan","key":"ref7"},{"key":"ref2","first-page":"1097","article-title":"Imagenet classification with deep convolutional networks","author":"krizhenvshky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref9","first-page":"562","article-title":"Deeply-supervised nets","author":"lee","year":"2015","journal-title":"Proc AISTATS"},{"key":"ref1","first-page":"436","volume":"521","author":"lecun","year":"2015","journal-title":"Deep Learning"},{"key":"ref20","first-page":"4278","article-title":"Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning [J]","author":"szegedy","year":"2016","journal-title":"National Conference on Artificial Intelligence"},{"journal-title":"Fast and accurate deep network learning by exponential linear units (ELUs)","year":"2015","author":"clevert","key":"ref22"},{"key":"ref21","first-page":"807","article-title":"Rectified linear units improve restricted Boltzmann machines","author":"nair","year":"0","journal-title":"Proceedings ICML 2010"},{"journal-title":"Parametric exponential linear unit for deep convolutional neural networks","year":"2016","author":"trottier","key":"ref24"},{"key":"ref23","first-page":"23","author":"grossmann","year":"0","journal-title":"Martin Stynes (2007) Numerical Treatment of Partial Differential Equations Springer Science & Business Media"},{"key":"ref26","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","author":"bishop","year":"1995","journal-title":"Neural Networks for Pattern Recognition Oxford University Press"},{"journal-title":"Batch Normalization Accelerating Deep Network Training by Reducing Internal Covariate Shift","year":"2015","author":"ioffe","key":"ref25"}],"event":{"name":"2017 4th International Conference on Systems and Informatics (ICSAI)","start":{"date-parts":[[2017,11,11]]},"location":"Hangzhou","end":{"date-parts":[[2017,11,13]]}},"container-title":["2017 4th International Conference on Systems and Informatics (ICSAI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8233022\/8248252\/08248500.pdf?arnumber=8248500","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,29]],"date-time":"2025-06-29T14:09:07Z","timestamp":1751206147000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8248500\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/icsai.2017.8248500","relation":{},"subject":[],"published":{"date-parts":[[2017,11]]}}}