{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,7]],"date-time":"2025-12-07T21:37:23Z","timestamp":1765143443134,"version":"3.37.3"},"reference-count":60,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100000923","name":"China Scholarship Council and Australian Research Council","doi-asserted-by":"publisher","award":["DP150104251"],"award-info":[{"award-number":["DP150104251"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2020]]},"DOI":"10.1109\/access.2020.2989331","type":"journal-article","created":{"date-parts":[[2020,4,21]],"date-time":"2020-04-21T20:12:20Z","timestamp":1587499940000},"page":"75957-75967","source":"Crossref","is-referenced-by-count":4,"title":["Scale-Aware Feature Network for Weakly Supervised Semantic Segmentation"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1759-2941","authenticated-orcid":false,"given":"Lian","family":"Xu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammed","family":"Bennamoun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Farid","family":"Boussaid","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1557-4907","authenticated-orcid":false,"given":"Ferdous","family":"Sohel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00745"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2888822"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00541"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2019.2914870"},{"key":"ref31","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":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00960"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2751140"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2017.2729019"},{"key":"ref35","article-title":"Neural machine translation by jointly learning to align and translate","author":"bahdanau","year":"2015","journal-title":"Proc ICLR"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00531"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00148"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2018.00097"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298780"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00733"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.191"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.2200\/S00822ED1V01Y201712COV015"},{"key":"ref20","first-page":"434","article-title":"TS2C: Tight box mining with surrounding segmentation context for weakly supervised object detection","author":"wei","year":"2018","journal-title":"Proc ECCV"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2019.2917224"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2018.2864891"},{"key":"ref24","article-title":"Striving for simplicity: The all convolutional net","author":"springenberg","year":"2014","journal-title":"ICLR Workshop Track"},{"key":"ref23","first-page":"818","article-title":"Visualizing and understanding convolutional networks","author":"zeiler","year":"2014","journal-title":"Proc ECCV"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298668"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46466-4_8"},{"article-title":"Pytorch: Tensors and dynamic neural networks in python with strong gpu acceleration","year":"2017","author":"paszke","key":"ref50"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.770"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01240-3_23"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.239"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2016.2636150"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.349"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2699184"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref52","first-page":"109","article-title":"Efficient inference in fully connected CRFS with Gaussian edge potentials","author":"kr\u00e4henb\u00fchl","year":"2011","journal-title":"Proc NIPS"},{"key":"ref10","first-page":"7420","article-title":"Transferable semi-supervised semantic segmentation","author":"xiao","year":"2018","journal-title":"Proc AAAI"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.319"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.74"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00523"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00147"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.687"},{"key":"ref16","article-title":"Semantic image segmentation with deep convolutional nets and fully connected Crfs","author":"chen","year":"2015","journal-title":"Proc ICLR"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532411"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.396"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2018.2875597"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.344"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.181"},{"key":"ref6","first-page":"549","article-title":"What&#x2019;s the point: Semantic segmentation with point supervision","author":"bearman","year":"2016","journal-title":"Proc ECCV"},{"key":"ref5","first-page":"1818","article-title":"Normal- ized cut loss for weakly-supervised CNN segmentation","author":"tang","year":"2018","journal-title":"Proc IEEE\/ CVF Conf Comput Vis Pattern Recognit"},{"key":"ref8","first-page":"4111","article-title":"Weakly supervised semantic segmentation using superpixel pooling network","author":"kwak","year":"2017","journal-title":"Proc AAAI"},{"key":"ref7","first-page":"695","article-title":"Seed, expand and constrain: Three principles for weakly-supervised image segmentation","author":"kolesnikov","year":"2016","journal-title":"Proc ECCV"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2011.6126343"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00759"},{"key":"ref46","first-page":"549","article-title":"Self-erasing network for integral object attention","author":"hou","year":"2018","journal-title":"Proc NIPS"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.563"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-009-0275-4"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2815688"},{"key":"ref42","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"arXiv 1409 1556"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.683"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00144"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.5244\/C.31.20"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/8948470\/09075085.pdf?arnumber=9075085","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,12,17]],"date-time":"2021-12-17T19:51:33Z","timestamp":1639770693000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9075085\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"references-count":60,"URL":"https:\/\/doi.org\/10.1109\/access.2020.2989331","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2020]]}}}