{"id":"https://openalex.org/W2905544033","doi":"https://doi.org/10.1109/tcsvt.2018.2886771","title":"Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network","display_name":"Blind Image Quality Assessment Using a Deep Bilinear Convolutional Neural Network","publication_year":2018,"publication_date":"2018-12-14","ids":{"openalex":"https://openalex.org/W2905544033","doi":"https://doi.org/10.1109/tcsvt.2018.2886771","mag":"2905544033"},"language":"en","primary_location":{"id":"doi:10.1109/tcsvt.2018.2886771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2018.2886771","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.02665","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101883961","display_name":"Weixia Zhang","orcid":"https://orcid.org/0000-0002-3634-2630"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weixia Zhang","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020029652","display_name":"Kede Ma","orcid":"https://orcid.org/0000-0001-8608-1128"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kede Ma","raw_affiliation_strings":["Center for Neural Science, New York University, New York, USA"],"raw_orcid":"https://orcid.org/0000-0001-8608-1128","affiliations":[{"raw_affiliation_string":"Center for Neural Science, New York University, New York, USA","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101705676","display_name":"Jia Yan","orcid":"https://orcid.org/0000-0001-5402-4698"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jia Yan","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5402-4698","affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109303609","display_name":"Dexiang Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dexiang Deng","raw_affiliation_strings":["Electronic Information School, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electronic Information School, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100420313","display_name":"Zhou Wang","orcid":"https://orcid.org/0000-0003-4413-4441"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zhou Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101883961"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":13.0468,"has_fulltext":false,"cited_by_count":893,"citation_normalized_percentile":{"value":0.98960154,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"30","issue":"1","first_page":"36","last_page":"47"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9908999800682068,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7931891679763794},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7408053278923035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7058903574943542},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.603326678276062},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5953289866447449},{"id":"https://openalex.org/keywords/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.554722785949707},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.5225807428359985},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5221540927886963},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5086632370948792},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4774363934993744},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.476068913936615},{"id":"https://openalex.org/keywords/stochastic-gradient-descent","display_name":"Stochastic gradient descent","score":0.46018582582473755},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3355209231376648},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2807656228542328},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15922889113426208},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08847463130950928}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7931891679763794},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7408053278923035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7058903574943542},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.603326678276062},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5953289866447449},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.554722785949707},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.5225807428359985},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5221540927886963},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5086632370948792},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4774363934993744},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.476068913936615},{"id":"https://openalex.org/C206688291","wikidata":"https://www.wikidata.org/wiki/Q7617819","display_name":"Stochastic gradient descent","level":3,"score":0.46018582582473755},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3355209231376648},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2807656228542328},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15922889113426208},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08847463130950928},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcsvt.2018.2886771","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcsvt.2018.2886771","pdf_url":null,"source":{"id":"https://openalex.org/S115173108","display_name":"IEEE Transactions on Circuits and Systems for Video Technology","issn_l":"1051-8215","issn":["1051-8215","1558-2205"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Circuits and Systems for Video Technology","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1907.02665","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.02665","pdf_url":"https://arxiv.org/pdf/1907.02665","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1907.02665","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.02665","pdf_url":"https://arxiv.org/pdf/1907.02665","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1157228107","display_name":null,"funder_award_id":"61701351","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W305983188","https://openalex.org/W592072200","https://openalex.org/W1522301498","https://openalex.org/W1580436348","https://openalex.org/W1580963329","https://openalex.org/W1606858007","https://openalex.org/W1665214252","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1963882359","https://openalex.org/W1974013408","https://openalex.org/W1977246677","https://openalex.org/W1982471090","https://openalex.org/W1983496390","https://openalex.org/W1987489060","https://openalex.org/W2007406620","https://openalex.org/W2013422999","https://openalex.org/W2031489346","https://openalex.org/W2051596736","https://openalex.org/W2052287864","https://openalex.org/W2082964377","https://openalex.org/W2085518012","https://openalex.org/W2104657103","https://openalex.org/W2108598243","https://openalex.org/W2126226185","https://openalex.org/W2141983208","https://openalex.org/W2148848374","https://openalex.org/W2151750630","https://openalex.org/W2156303437","https://openalex.org/W2161907179","https://openalex.org/W2163370434","https://openalex.org/W2171349048","https://openalex.org/W2194775991","https://openalex.org/W2294857031","https://openalex.org/W2342662179","https://openalex.org/W2466606639","https://openalex.org/W2473697052","https://openalex.org/W2546855109","https://openalex.org/W2556068545","https://openalex.org/W2563786098","https://openalex.org/W2566149141","https://openalex.org/W2618902759","https://openalex.org/W2764293197","https://openalex.org/W2766426813","https://openalex.org/W2767836774","https://openalex.org/W2768340063","https://openalex.org/W2953066166","https://openalex.org/W2962676454","https://openalex.org/W2962835968","https://openalex.org/W2963066927","https://openalex.org/W2963383024","https://openalex.org/W2963918210","https://openalex.org/W2964121744","https://openalex.org/W3098560717","https://openalex.org/W3100404621","https://openalex.org/W3100498948","https://openalex.org/W3102733987","https://openalex.org/W4211253871","https://openalex.org/W4239072543","https://openalex.org/W6617788180","https://openalex.org/W6637242042","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6647225686","https://openalex.org/W6671235838","https://openalex.org/W6682508104","https://openalex.org/W6682864246","https://openalex.org/W6729689515","https://openalex.org/W6745059213"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W2388888344"],"abstract_inverted_index":{"We":[0,99],"propose":[1],"a":[2,43,65,75,95,109],"deep":[3,26],"bilinear":[4],"model":[5,21,123],"for":[6,13,79,94],"blind":[7],"image":[8,81],"quality":[9,97],"assessment":[10],"that":[11,120],"works":[12],"both":[14,128],"synthetically":[15],"and":[16,50,130,148],"authentically":[17],"distorted":[18],"images.":[19],"Our":[20],"constitutes":[22],"two":[23,33,85],"streams":[24],"of":[25,53,74,111,139],"convolutional":[27],"neural":[28],"networks":[29],"(CNNs),":[30],"specializing":[31],"in":[32],"distortion":[34,48],"scenarios":[35],"separately.":[36],"For":[37,68],"synthetic":[38,129],"distortions,":[39,70],"we":[40,71,135],"first":[41],"pre-train":[42,76],"CNN":[44,77],"to":[45],"classify":[46],"the":[47,51,80,101,105,121,137,143,153],"type":[49],"level":[52],"an":[54],"input":[55],"image,":[56],"whose":[57],"ground":[58],"truth":[59],"label":[60],"is":[61],"readily":[62],"available":[63],"at":[64],"large":[66],"scale.":[67],"authentic":[69,131],"make":[72],"use":[73],"(VGG-16)":[78],"classification":[82],"task.":[83],"The":[84,115],"feature":[86],"sets":[87],"are":[88],"bilinearly":[89],"pooled":[90],"into":[91],"one":[92],"representation":[93],"final":[96],"prediction.":[98],"fine-tune":[100],"whole":[102],"network":[103],"on":[104,127,142],"target":[106],"databases":[107],"using":[108,152],"variant":[110],"stochastic":[112],"gradient":[113],"descent.":[114],"extensive":[116],"experimental":[117],"results":[118],"show":[119],"proposed":[122],"achieves":[124],"state-of-the-art":[125],"performance":[126],"IQA":[132],"databases.":[133],"Furthermore,":[134],"verify":[136],"generalizability":[138],"our":[140],"method":[141],"large-scale":[144],"Waterloo":[145],"Exploration":[146],"Database,":[147],"demonstrate":[149],"its":[150],"competitiveness":[151],"group":[154],"maximum":[155],"differentiation":[156],"competition":[157],"methodology.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":62},{"year":2025,"cited_by_count":206},{"year":2024,"cited_by_count":200},{"year":2023,"cited_by_count":164},{"year":2022,"cited_by_count":138},{"year":2021,"cited_by_count":76},{"year":2020,"cited_by_count":42},{"year":2019,"cited_by_count":5}],"updated_date":"2026-06-05T09:01:59.212387","created_date":"2018-12-22T00:00:00"}
