{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:57:14Z","timestamp":1760597834057,"version":"3.37.3"},"reference-count":33,"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:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Image Process."],"published-print":{"date-parts":[[2018,11]]},"DOI":"10.1109\/tip.2018.2855966","type":"journal-article","created":{"date-parts":[[2018,7,13]],"date-time":"2018-07-13T18:46:44Z","timestamp":1531507604000},"page":"5553-5562","source":"Crossref","is-referenced-by-count":29,"title":["Quality Robust Mixtures of Deep Neural Networks"],"prefix":"10.1109","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8916-6071","authenticated-orcid":false,"given":"Samuel F.","family":"Dodge","sequence":"first","affiliation":[]},{"given":"Lina J.","family":"Karam","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.71"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2013.2283400"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2010.2043888"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.81"},{"journal-title":"Dirty pixels Optimizing image classification architectures for raw sensor data","year":"2016","author":"diamond","key":"ref10"},{"journal-title":"Towards robust deep neural networks with BANG","year":"2016","author":"rozsa","key":"ref11"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.485"},{"journal-title":"Deepcorrect Correcting dnn models against image distortions","year":"2017","author":"borkar","key":"ref13"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref15","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref18","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 Stat"},{"key":"ref19","first-page":"372","article-title":"A method of solving a convex programming problem with convergence rate \n$O(1\/k^{2})$","volume":"27","author":"nesterov","year":"1983","journal-title":"Sov Math Doklady"},{"key":"ref28","first-page":"1","article-title":"Edge-based blur kernel estimation using patch priors","author":"sun","year":"2013","journal-title":"Proc IEEE Int Conf Comput Photogr"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1991.3.1.79"},{"key":"ref27","article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and Huffman coding","author":"han","year":"2016","journal-title":"Proc Int Conf Learn Represent"},{"journal-title":"Examining the impact of blur on recognition by convolutional networks","year":"2016","author":"vasiljevic","key":"ref3"},{"key":"ref6","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298965"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/QoMEX.2016.7498955"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref7","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":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7952349"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.60"},{"key":"ref1","article-title":"Intriguing properties of neural networks","author":"szegedy","year":"2014","journal-title":"Proc Int Conf Learn Represent"},{"journal-title":"A software package for sequential quadratic programming","year":"1988","author":"kraft","key":"ref20"},{"journal-title":"Why M heads are better than one Training a diverse ensemble of deep networks","year":"2015","author":"lee","key":"ref22"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298701"},{"journal-title":"Caltech-256 Object Category Dataset","year":"2007","author":"griffin","key":"ref24"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.cviu.2005.09.012"},{"key":"ref26","first-page":"3642","article-title":"Multi-column deep neural networks for image classification","author":"ciregan","year":"2012","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206537"}],"container-title":["IEEE Transactions on Image Processing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/83\/8421670\/08410945.pdf?arnumber=8410945","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T16:29:30Z","timestamp":1642004970000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8410945\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,11]]},"references-count":33,"journal-issue":{"issue":"11"},"URL":"https:\/\/doi.org\/10.1109\/tip.2018.2855966","relation":{},"ISSN":["1057-7149","1941-0042"],"issn-type":[{"type":"print","value":"1057-7149"},{"type":"electronic","value":"1941-0042"}],"subject":[],"published":{"date-parts":[[2018,11]]}}}