{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T03:14:02Z","timestamp":1776482042637,"version":"3.51.2"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"11","license":[{"start":{"date-parts":[[2018,11,1]],"date-time":"2018-11-01T00:00:00Z","timestamp":1541030400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100000739","name":"University of Southampton","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000739","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2018,11]]},"DOI":"10.1109\/tnnls.2018.2805098","type":"journal-article","created":{"date-parts":[[2018,3,6]],"date-time":"2018-03-06T19:16:44Z","timestamp":1520363804000},"page":"5475-5485","source":"Crossref","is-referenced-by-count":89,"title":["Deep Cascade Learning"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6501-7482","authenticated-orcid":false,"given":"Enrique S.","family":"Marquez","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2921-4283","authenticated-orcid":false,"given":"Jonathon S.","family":"Hare","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mahesan","family":"Niranjan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","first-page":"1","article-title":"Compressing neural networks with the hashing trick","author":"chen","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref32","first-page":"442","article-title":"Tensorizing neural networks","author":"novikov","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref31","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref30","first-page":"1","article-title":"Rectified linear units improve restricted boltzmann machines","author":"nair","year":"2010","journal-title":"Proc 27th Int Conf Mach Learn"},{"key":"ref35","author":"cortes","year":"2016","journal-title":"AdaNet Adaptive Structural Learning of Artificial Neural Networks"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"1265","DOI":"10.1162\/NECO_a_00848","article-title":"An infinite restricted Boltzmann machine","volume":"28","author":"c\u00f4t\u00e9","year":"2016","journal-title":"Neural Comput"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553453"},{"key":"ref12","author":"he","year":"2015","journal-title":"Deep residual learning for image recognition"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref14","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.220"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2012.6288864"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2749977"},{"key":"ref28","author":"larsson","year":"2016","journal-title":"Fractalnet Ultra-deep neural networks without residuals"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1996.8.4.855"},{"key":"ref27","author":"springenberg","year":"2014","journal-title":"Striving for simplicity The all convolutional net"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1993.5.6.954"},{"key":"ref6","article-title":"Deep compression: Compressing deep neural network with pruning, trained quantization and Huffman coding","volume":"abs 1510 149","author":"han","year":"2015","journal-title":"CoRR"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299173"},{"key":"ref5","author":"shadafan","year":"1995","journal-title":"Sequential Training of Multilayer Perceptron Classifiers"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/BF00344251"},{"key":"ref7","author":"rastegari","year":"2016","journal-title":"Xnor-net Imagenet classification using binary convolutional neural networks"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.2.213"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref1","first-page":"524","article-title":"Advances in neural information processing systems","author":"fahlman","year":"1990","journal-title":"The cascade-correlation learning architecture"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2017.2749965"},{"key":"ref22","author":"huang","year":"2016","journal-title":"Deep networks with stochastic depth"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref24","first-page":"550","article-title":"Residual networks behave like ensembles of relatively shallow networks","author":"veit","year":"2016","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proceedings of the 32nd Intl Conf on Machine Learning"},{"key":"ref26","author":"simonyan","year":"2014","journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition"},{"key":"ref25","author":"duda","year":"2012","journal-title":"Pattern Classification"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8495104\/08307262.pdf?arnumber=8307262","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,26]],"date-time":"2022-01-26T21:01:25Z","timestamp":1643230885000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8307262\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11]]},"references-count":35,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2018.2805098","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,11]]}}}