{"id":"https://openalex.org/W4309713922","doi":"https://doi.org/10.1080/09540091.2022.2147902","title":"Semantic-aware multi-task learning for image aesthetic quality assessment","display_name":"Semantic-aware multi-task learning for image aesthetic quality assessment","publication_year":2022,"publication_date":"2022-11-22","ids":{"openalex":"https://openalex.org/W4309713922","doi":"https://doi.org/10.1080/09540091.2022.2147902"},"language":"en","primary_location":{"id":"doi:10.1080/09540091.2022.2147902","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2022.2147902","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2147902?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2147902?needAccess=true","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100578239","display_name":"Weiliang Yan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weiliang Yan","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100379940","display_name":"Yuqing Li","orcid":"https://orcid.org/0000-0003-0816-5777"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuqing Li","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081110905","display_name":"Huan Yang","orcid":"https://orcid.org/0000-0001-5810-0248"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Huan Yang","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059041277","display_name":"Baoxiang Huang","orcid":"https://orcid.org/0000-0002-0380-419X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baoxiang Huang","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113828890","display_name":"Zhenkuan Pan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhenkuan Pan","raw_affiliation_strings":["College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Qingdao University, Qingdao, People\u2019s Republic of China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5081110905"],"corresponding_institution_ids":[],"apc_list":{"value":1270,"currency":"USD","value_usd":1270},"apc_paid":{"value":1270,"currency":"USD","value_usd":1270},"fwci":0.8809,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.74548184,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"34","issue":"1","first_page":"2689","last_page":"2713"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T11165","display_name":"Image and Video Quality Assessment","score":0.9969000220298767,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8473304510116577},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6367089748382568},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6263129711151123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5996667146682739},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.5478506088256836},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5386654138565063},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5236161351203918},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48268628120422363},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.47990381717681885},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.46421316266059875},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4488091468811035},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4436846971511841},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4309671223163605},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41804876923561096},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38296636939048767},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3540896773338318}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8473304510116577},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6367089748382568},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6263129711151123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5996667146682739},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.5478506088256836},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5386654138565063},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5236161351203918},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48268628120422363},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.47990381717681885},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.46421316266059875},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4488091468811035},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4436846971511841},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4309671223163605},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41804876923561096},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38296636939048767},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3540896773338318},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/09540091.2022.2147902","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2022.2147902","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2147902?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e61998bd3ba24d84a01f5b6263f7ed13","is_oa":false,"landing_page_url":"https://doaj.org/article/e61998bd3ba24d84a01f5b6263f7ed13","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Connection Science, Vol 34, Iss 1, Pp 2689-2713 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/09540091.2022.2147902","is_oa":true,"landing_page_url":"https://doi.org/10.1080/09540091.2022.2147902","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/09540091.2022.2147902?needAccess=true","source":{"id":"https://openalex.org/S4210188800","display_name":"Connection Science","issn_l":"0954-0091","issn":["0954-0091","1360-0494"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Connection Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7152828753","display_name":null,"funder_award_id":"ZR2021MD001","funder_id":"https://openalex.org/F4320324174","funder_display_name":"Natural Science Foundation of Shandong Province"}],"funders":[{"id":"https://openalex.org/F4320324174","display_name":"Natural Science Foundation of Shandong Province","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4309713922.pdf","grobid_xml":"https://content.openalex.org/works/W4309713922.grobid-xml"},"referenced_works_count":52,"referenced_works":["https://openalex.org/W1511924373","https://openalex.org/W1587773003","https://openalex.org/W1920280450","https://openalex.org/W2003635569","https://openalex.org/W2009678853","https://openalex.org/W2048835603","https://openalex.org/W2056380823","https://openalex.org/W2078807908","https://openalex.org/W2108598243","https://openalex.org/W2194775991","https://openalex.org/W2217895792","https://openalex.org/W2243549423","https://openalex.org/W2359978643","https://openalex.org/W2417288846","https://openalex.org/W2467531333","https://openalex.org/W2514622527","https://openalex.org/W2565639579","https://openalex.org/W2604528050","https://openalex.org/W2734838866","https://openalex.org/W2754213847","https://openalex.org/W2774049169","https://openalex.org/W2775725209","https://openalex.org/W2798868169","https://openalex.org/W2896399498","https://openalex.org/W2897926040","https://openalex.org/W2904572228","https://openalex.org/W2910628332","https://openalex.org/W2963156339","https://openalex.org/W2963430933","https://openalex.org/W2963722311","https://openalex.org/W2965318645","https://openalex.org/W2970379460","https://openalex.org/W2976886057","https://openalex.org/W2995019771","https://openalex.org/W3003957020","https://openalex.org/W3013928520","https://openalex.org/W3016197248","https://openalex.org/W3025478955","https://openalex.org/W3035523707","https://openalex.org/W3035595647","https://openalex.org/W3088478528","https://openalex.org/W3093185587","https://openalex.org/W3093501041","https://openalex.org/W3094897602","https://openalex.org/W3103635814","https://openalex.org/W3107944836","https://openalex.org/W3121625413","https://openalex.org/W3164459664","https://openalex.org/W3171472210","https://openalex.org/W3174795132","https://openalex.org/W3194293177","https://openalex.org/W3210514413"],"related_works":["https://openalex.org/W4312417841","https://openalex.org/W4321369474","https://openalex.org/W2731899572","https://openalex.org/W3133861977","https://openalex.org/W4200173597","https://openalex.org/W4299822940","https://openalex.org/W2279398222","https://openalex.org/W3156786002","https://openalex.org/W4366492315","https://openalex.org/W3203013933"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"image":[3,32,38,72,108],"aesthetic":[4,28,39,51,73,101,109],"quality":[5,29,74,110],"assessment":[6,111],"has":[7],"attracted":[8],"considerable":[9],"attention":[10,126],"due":[11],"to":[12,94,141,145,153,156],"the":[13,23,46,50,104,125,143,148,158,166,173,178],"massive":[14],"growth":[15],"of":[16,30,52,86,107,151,160,177],"digital":[17],"images":[18,53],"in":[19,77,92,117],"social":[20],"platforms":[21],"and":[22,45,99,113,169,175],"Internet.":[24],"However,":[25],"automatically":[26],"assessing":[27],"an":[31],"is":[33,40,75,139],"a":[34,63,96,118,131],"challenging":[35],"task,":[36],"because":[37],"affected":[41],"by":[42,123],"various":[43],"factors,":[44],"criteria":[47],"for":[48,70],"judging":[49],"with":[54,130],"diverse":[55],"semantic":[56,114,128],"information":[57,129],"are":[58],"different.":[59],"To":[60],"this":[61,78],"end,":[62],"Semantic-Aware":[64],"Multi-task":[65],"convolution":[66],"neural":[67],"network":[68,81,144],"(SAM-CNN)":[69],"evaluating":[71],"proposed":[76,179],"paper.":[79],"The":[80],"can":[82],"fuse":[83],"intermediate":[84],"features":[85,152],"different":[87,90],"layers":[88,138],"at":[89],"scales":[91],"CNN":[93],"obtain":[95],"more":[97],"comprehensive":[98],"accurate":[100],"expression,":[102],"under":[103],"joint":[105],"supervision":[106],"task":[112,116],"classification":[115],"multi-task":[119],"learning":[120],"manner.":[121],"Besides,":[122],"applying":[124],"mechanism,":[127],"large":[132],"receptive":[133],"field":[134],"extracted":[135],"from":[136],"deep":[137],"utilised":[140],"guide":[142],"focus":[146],"on":[147,165],"key":[149],"parts":[150],"be":[154],"fused,":[155],"improve":[157],"effectiveness":[159,174],"feature":[161],"fusion.":[162],"Experimental":[163],"results":[164],"AVA":[167],"dataset":[168,171],"Photo.net":[170],"demonstrate":[172],"superiority":[176],"SAM-CNN.":[180]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-06-20T20:08:15.867695","created_date":"2025-10-10T00:00:00"}