{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T15:22:16Z","timestamp":1783437736450,"version":"3.54.6"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1641042"],"award-info":[{"award-number":["1641042"]}],"id":[{"id":"10.13039\/100000001","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":[[2019,9]]},"DOI":"10.1109\/tnnls.2018.2885972","type":"journal-article","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T00:43:15Z","timestamp":1546994595000},"page":"2650-2661","source":"Crossref","is-referenced-by-count":79,"title":["Regularizing Deep Neural Networks by Enhancing Diversity in Feature Extraction"],"prefix":"10.1109","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7341-8799","authenticated-orcid":false,"given":"Babajide O.","family":"Ayinde","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5314-3908","authenticated-orcid":false,"given":"Tamer","family":"Inanc","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6622-534X","authenticated-orcid":false,"given":"Jacek M.","family":"Zurada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref39","author":"kingma","year":"2014","journal-title":"Adam A method for stochastic optimization"},{"key":"ref38","author":"abadi","year":"2015","journal-title":"Tensorflow Large-scale machine learning on heterogeneous distributed systems"},{"key":"ref33","first-page":"7","article-title":"Combined object categorization and segmentation with an implicit shape model","volume":"2","author":"leibe","year":"2004","journal-title":"Proc Workshop Stat Learn Comput Vis (ECCV)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2002.1183896"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/RT.2008.4634626"},{"key":"ref30","article-title":"Learning multiple layers of features from tiny images","author":"krizhevsky","year":"2009"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D15-1075"},{"key":"ref36","author":"lecun","year":"1998","journal-title":"The MNIST Database of Handwritten Digits"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2608001"},{"key":"ref34","article-title":"Intelligent and optimal normalized correlation for high-speed pattern matching","author":"manickam","year":"2000"},{"key":"ref10","author":"van den oord","year":"2016","journal-title":"WaveNet A Generative Model for Raw Audio"},{"key":"ref40","author":"huang","year":"2016","journal-title":"Densely Connected Convolutional Networks"},{"key":"ref11","first-page":"448","article-title":"Batch normalization: Accelerating deep network training by reducing internal covariate shift","author":"ioffe","year":"2015","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref12","first-page":"249","article-title":"Understanding the difficulty of training deep feedforward neural networks","author":"glorot","year":"2010","journal-title":"Proc 13th Int Conf Artif Intell Statist"},{"key":"ref13","author":"mishkin","year":"2015","journal-title":"All you need is a good init"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1992.4.4.473"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2017.2747861"},{"key":"ref16","first-page":"1058","article-title":"Regularization of neural networks using dropconnect","author":"wan","year":"2013","journal-title":"Proc 30th Int Conf Mach Learn"},{"key":"ref17","first-page":"99","article-title":"Slow, decorrelated features for pretraining complex cell-like networks","author":"bengio","year":"2009","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6639015"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/78.553484"},{"key":"ref28","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref27","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref3","author":"rodr\u00edguez","year":"2016","journal-title":"Regularizing CNNs with locally constrained decorrelations"},{"key":"ref6","author":"jozefowicz","year":"2016","journal-title":"Exploring the limits of language modeling"},{"key":"ref29","author":"belharbi","year":"2017","journal-title":"Neural networks regularization through class-wise invariant representation learning"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2013.6638947"},{"key":"ref7","author":"shazeer","year":"2017","journal-title":"Outrageously large neural networks The sparsely-gated mixture-of-experts layer"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"ref9","first-page":"1764","article-title":"Towards end-to-end speech recognition with recurrent neural networks","author":"graves","year":"2014","journal-title":"Proc 31st Int Conf Mach Learn"},{"key":"ref1","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/W17-5307"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"key":"ref45","author":"liu","year":"2016","journal-title":"Learning natural language inference using bidirectional LSTM model and inner-attention"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.514"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P16-1139"},{"key":"ref21","author":"hinton","year":"2015","journal-title":"Distilling the knowledge in a neural network"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1186\/s13637-016-0055-8"},{"key":"ref41","first-page":"646","article-title":"Deep networks with stochastic depth","author":"huang","year":"0","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref23","author":"pereyra","year":"2017","journal-title":"Regularizing neural networks by penalizing confident output disrributions"},{"key":"ref44","author":"munkhdalai","year":"2016","journal-title":"Neural semantic encoders"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2017.04.012"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.3115\/v1\/D14-1162"},{"key":"ref25","author":"dundar","year":"2015","journal-title":"Convolutional clustering for unsupervised learning"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"https:\/\/ieeexplore.ieee.org\/ielaam\/5962385\/8809853\/8603826-aam.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8809853\/08603826.pdf?arnumber=8603826","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:55:57Z","timestamp":1657745757000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8603826\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":47,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2018.2885972","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9]]}}}