{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,22]],"date-time":"2025-11-22T11:15:31Z","timestamp":1763810131269,"version":"build-2065373602"},"reference-count":23,"publisher":"IEEE","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":"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"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1109\/icip.2019.8803544","type":"proceedings-article","created":{"date-parts":[[2019,8,26]],"date-time":"2019-08-26T19:32:48Z","timestamp":1566847968000},"page":"4290-4294","source":"Crossref","is-referenced-by-count":20,"title":["Lightweight Monocular Depth Estimation Model by Joint End-to-End Filter Pruning"],"prefix":"10.1109","author":[{"given":"Sara","family":"Elkerdawy","sequence":"first","affiliation":[]},{"given":"Hong","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Nilanjan","family":"Ray","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.304"},{"key":"ref11","article-title":"Estimating depth from monocular images as classification using deep fully convolutional residual networks","author":"cao","year":"2017","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.596"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00214"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2012.6248074"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.700"},{"key":"ref16","first-page":"5515","article-title":"Deepstereo: Learning to predict new views from the world’s imagery","author":"flynn","year":"2016","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref17","first-page":"842","article-title":"Deep3d: Fully automatic 2d-to-3d video conversion with deep convolutional neural networks","author":"xie","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"ref19","article-title":"Adam: A method for stochastic optimization","volume":"abs 1412 6980","author":"kingma","year":"2014","journal-title":"CoRR"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.155"},{"article-title":"Improving neural networks by preventing co-adaptation of feature detectors","year":"2012","author":"hinton","key":"ref3"},{"article-title":"Pruning filters for efficient convnets","year":"2016","author":"li","key":"ref6"},{"article-title":"Distilling the knowledge in a neural network","year":"2015","author":"hinton","key":"ref5"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2008.132"},{"article-title":"Estimating or propagating gradients through stochastic neurons for conditional computation","year":"2013","author":"bengio","key":"ref7"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593814"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.699"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/1186822.1073232"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.350"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2505283"},{"key":"ref21","first-page":"173","article-title":"Semi-global matchingmotivation, developments and applications","volume":"11","author":"hirschm\u00fcller","year":"2011","journal-title":"Photogrammetric Week"},{"key":"ref23","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"}],"event":{"name":"2019 IEEE International Conference on Image Processing (ICIP)","start":{"date-parts":[[2019,9,22]]},"location":"Taipei, Taiwan","end":{"date-parts":[[2019,9,25]]}},"container-title":["2019 IEEE International Conference on Image Processing (ICIP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8791230\/8799366\/08803544.pdf?arnumber=8803544","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T14:46:16Z","timestamp":1658155576000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8803544\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1109\/icip.2019.8803544","relation":{},"subject":[],"published":{"date-parts":[[2019,9]]}}}