{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:21:17Z","timestamp":1773415277906,"version":"3.50.1"},"reference-count":62,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,6,1]],"date-time":"2019-06-01T00:00:00Z","timestamp":1559347200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100010669","name":"H2020 LEIT Information and Communication Technologies","doi-asserted-by":"publisher","award":["H2020-687786 InVID"],"award-info":[{"award-number":["H2020-687786 InVID"]}],"id":[{"id":"10.13039\/100010669","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007065","name":"Nvidia","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007065","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Circuits Syst. Video Technol."],"published-print":{"date-parts":[[2019,6]]},"DOI":"10.1109\/tcsvt.2018.2848458","type":"journal-article","created":{"date-parts":[[2018,6,18]],"date-time":"2018-06-18T18:27:21Z","timestamp":1529346441000},"page":"1631-1644","source":"Crossref","is-referenced-by-count":50,"title":["Implicit and Explicit Concept Relations in Deep Neural Networks for Multi-Label Video\/Image Annotation"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8537-9504","authenticated-orcid":false,"given":"Foteini","family":"Markatopoulou","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0121-4364","authenticated-orcid":false,"given":"Vasileios","family":"Mezaris","sequence":"additional","affiliation":[]},{"given":"Ioannis","family":"Patras","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref39","first-page":"25","article-title":"Max-margin Markov networks","author":"taskar","year":"2003","journal-title":"Proc 16th Int Conf Neural Inf Process Syst (NIPS)"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2013.104"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"2029","DOI":"10.1016\/j.patcog.2009.01.023","article-title":"Image annotation using multi-label correlated green&#x2019;s function","author":"wang","year":"2009","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2011.5995379"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2011.2169269"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1291233.1291245"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1145\/2578726.2578741"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/s11229-008-9348-0"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/2396761.2398532"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835930"},{"key":"ref60","author":"jia","year":"2014","journal-title":"Caffe Convolutional Architecture for Fast Feature Embedding"},{"key":"ref62","first-page":"1879","article-title":"Segmentation as selective search for object recognition","author":"sm eulders","year":"2011","journal-title":"Proc ICCV"},{"key":"ref61","author":"blanken","year":"2005","journal-title":"Multimedia Retrieval"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.138"},{"key":"ref27","first-page":"48","author":"deng","year":"2014","journal-title":"Large-Scale Object Classification Using Label Relation Graphs"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TETC.2015.2418714"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-51811-4_9"},{"key":"ref1","author":"everingham","year":"2007","journal-title":"The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results"},{"key":"ref20","first-page":"702","article-title":"Clustered multi-task learning via alternating structure optimization","author":"zhou","year":"2011","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2016.7532344"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2015.7350949"},{"key":"ref24","article-title":"A unified perspective on multi-domain and multi-task learning","author":"yang","year":"2015","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10599-4_7"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2011.273"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2003.1221649"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2532719"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2016.2539541"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/1390334.1390437"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-015-0816-y"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1145\/1646396.1646452"},{"key":"ref56","author":"everingham","year":"2012","journal-title":"The PASCAL Visual Object Classes Challenge 2012 (VOC2012) Results"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2013.2265601"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2009.2017400"},{"key":"ref53","article-title":"TRECVID 2014&#x2014;An overview of the goals, tasks, data, evaluation mechanisms, and metrics","author":"over","year":"2013"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2015.2511543"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2491929"},{"key":"ref40","first-page":"567","article-title":"Fast and balanced: Efficient label tree learning for large scale object recognition","author":"deng","year":"2011","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2016.2612829"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/FG.2017.86"},{"key":"ref14","first-page":"41","article-title":"Multi-task feature learning","author":"argyriou","year":"2007","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref15","article-title":"Multi-task feature selection","author":"obozinski","year":"0"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2014.7025860"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014067"},{"key":"ref18","first-page":"135","article-title":"Bayesian multitask learning with latent hierarchies","author":"daum\u00e9","year":"2009","journal-title":"Proc Conf Uncertainty in Artificial Intelligence (UAI)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-007-5040-8"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_28"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.469"},{"key":"ref6","first-page":"964","article-title":"A dirty model for multi-task learning","author":"jalali","year":"2010","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.120"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2964284.2967271"},{"key":"ref7","first-page":"1383","article-title":"Learning task grouping and overlap in multi-task learning","author":"kumar","year":"2012","journal-title":"Proc 29th Int Conf Mach Learn (ICML)"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2013.2276704"},{"key":"ref9","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014","journal-title":"CoRR"},{"key":"ref46","first-page":"3320","article-title":"How transferable are features in deep neural networks?","author":"yosinski","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst (NIPS)"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2426707"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.299"},{"key":"ref47","article-title":"Deep multi-task representation learning: A tensor factorisation approach","author":"yang","year":"2017","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref42","article-title":"Fully connected deep structured networks","author":"schwing","year":"2015","journal-title":"CoRR"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2013.11.007"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.179"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.516"}],"container-title":["IEEE Transactions on Circuits and Systems for Video Technology"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/76\/8727555\/08387768.pdf?arnumber=8387768","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,13]],"date-time":"2022-07-13T20:56:34Z","timestamp":1657745794000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8387768\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,6]]},"references-count":62,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tcsvt.2018.2848458","relation":{},"ISSN":["1051-8215","1558-2205"],"issn-type":[{"value":"1051-8215","type":"print"},{"value":"1558-2205","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,6]]}}}