{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T15:55:23Z","timestamp":1730303723541,"version":"3.28.0"},"reference-count":66,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,3,1]],"date-time":"2020-03-01T00:00:00Z","timestamp":1583020800000},"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":[[2020,3]]},"DOI":"10.1109\/wacv45572.2020.9093354","type":"proceedings-article","created":{"date-parts":[[2020,5,14]],"date-time":"2020-05-14T23:41:09Z","timestamp":1589499669000},"page":"1667-1677","source":"Crossref","is-referenced-by-count":1,"title":["QUICKSAL: A small and sparse visual saliency model for efficient inference in resource constrained hardware"],"prefix":"10.1109","author":[{"given":"Vignesh","family":"Ramanathan","sequence":"first","affiliation":[]},{"given":"Pritesh","family":"Dwivedi","sequence":"additional","affiliation":[]},{"given":"Bharath","family":"Katabathuni","sequence":"additional","affiliation":[]},{"given":"Anirban","family":"Chakraborty","sequence":"additional","affiliation":[]},{"given":"Chetan Singh","family":"Thakur","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2019.8702200"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/BioCAS.2013.6679631"},{"key":"ref33","first-page":"21","article-title":"Ssd: Single shot multibox detector","author":"liu","year":"2016","journal-title":"European Conference on Computer Vision"},{"key":"ref32","first-page":"353","article-title":"Learning to detect a salient object","volume":"33","author":"liu","year":"2010","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"ref31","first-page":"362","article-title":"Predicting eye fixations using convolutional neural networks","author":"liu","year":"2015","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.80"},{"key":"ref37","first-page":"379","article-title":"Designing neural networks using genetic algorithms","volume":"89","author":"miller","year":"1989","journal-title":"ICGA"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.39"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/957013.957094"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.698"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.153"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1145\/1180639.1180824"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2013.407"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.31"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.43"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.32"},{"article-title":"Pruning filters for efficient convnets","year":"2016","author":"li","key":"ref27"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298731"},{"article-title":"Neural architecture search with reinforcement learning","year":"2016","author":"zoph","key":"ref66"},{"key":"ref29","first-page":"19","article-title":"Progressive neural architecture search","author":"liu","year":"2018","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV)"},{"key":"ref2","first-page":"2654","article-title":"Do deep nets really need to be deep?","author":"ba","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref1","first-page":"265","article-title":"Tensor-flow: A system for large-scale machine learning","author":"abadi","year":"2016","journal-title":"12th USENIX Symposium on Operating Systems Design and Implementation ( OSDI 16)"},{"key":"ref20","first-page":"2016","article-title":"Neural architecture search with bayesian optimisation and optimal transport","author":"kandasamy","year":"2018","journal-title":"Advances in neural information processing systems"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.623"},{"key":"ref21","first-page":"1097","article-title":"Imagenet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"},{"key":"ref24","first-page":"2554","article-title":"Fast convnets using groupwise brain damage","author":"lebedev","year":"2016","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"article-title":"Deep gaze i: Boosting saliency prediction with feature maps trained on imagenet","year":"2014","author":"k\u00fcmmerer","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.58"},{"key":"ref25","first-page":"5455","article-title":"Visual saliency based on multiscale deep features","author":"li","year":"2015","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"2014","author":"simonyan","key":"ref50"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.164"},{"key":"ref58","first-page":"4019","article-title":"A stage-wise refinement model for detecting salient objects in images","author":"wang","year":"2017","journal-title":"Proceedings of the IEEE International Conference on Computer Vision"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46493-0_50"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298938"},{"key":"ref55","first-page":"1","article-title":"A discriminative regional feature integration approach","author":"wang","year":"2017","journal-title":"IEEE Int J Comput Vis"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.256"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1017\/S0140525X00072484"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2017.8050868"},{"article-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks","year":"2018","author":"frankle","key":"ref10"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.668"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.178"},{"article-title":"Deep compression: Compressing deep neural networks with pruning, trained quantization and huffman coding","year":"2015","author":"han","key":"ref12"},{"key":"ref13","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","author":"han","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref14","first-page":"447","article-title":"Hypercolumns for object segmentation and fine-grained localization","author":"hariharan","year":"2015","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Distilling the knowledge in a neural network","year":"2015","author":"hinton","key":"ref16"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ISSCC.2014.6757323"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.563"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/34.730558"},{"journal-title":"Perception and Communication","year":"2013","author":"broadbent","key":"ref4"},{"key":"ref3","first-page":"1","article-title":"Salient object detection: A survey","author":"borji","year":"2014","journal-title":"Computational Visual Media"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2014.2345401"},{"key":"ref5","article-title":"Semantic image segmentation with deep convolutional nets and fully connected crfs","author":"chen","year":"2015","journal-title":"ICLRE"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"article-title":"Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1","year":"2016","author":"courbariaux","key":"ref7"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref9","first-page":"1269","article-title":"Exploiting linear structure within convolutional networks for efficient evaluation","author":"denton","year":"2014","journal-title":"Advances in neural information processing systems"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.91"},{"key":"ref45","first-page":"525","article-title":"Xnornet: Imagenet classification using binary convolutional neural networks","author":"rastegari","year":"2016","journal-title":"European Conference on Computer Vision"},{"article-title":"Fitnets: Hints for thin deep nets","year":"2014","author":"romero","key":"ref48"},{"key":"ref47","first-page":"91","article-title":"Faster r-cnn: Towards real-time object detection with region proposal networks","volume":"28","author":"ren","year":"2015","journal-title":"Advances in neural information processing systems"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.203"},{"key":"ref41","first-page":"27","article-title":"Enhancing salient object segmentation through attention","author":"pahuja","year":"2019","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops"},{"key":"ref44","first-page":"110","article-title":"Saliency detection via cellular automata","author":"qin","year":"2015","journal-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition"},{"article-title":"Automatic differentiation in pytorch","year":"2017","author":"paszke","key":"ref43"}],"event":{"name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","start":{"date-parts":[[2020,3,1]]},"location":"Snowmass Village, CO, USA","end":{"date-parts":[[2020,3,5]]}},"container-title":["2020 IEEE Winter Conference on Applications of Computer Vision (WACV)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9087828\/9093261\/09093354.pdf?arnumber=9093354","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,30]],"date-time":"2022-06-30T11:17:57Z","timestamp":1656587877000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9093354\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3]]},"references-count":66,"URL":"https:\/\/doi.org\/10.1109\/wacv45572.2020.9093354","relation":{},"subject":[],"published":{"date-parts":[[2020,3]]}}}