{"id":"https://openalex.org/W4280563717","doi":"https://doi.org/10.1109/tcyb.2022.3169017","title":"MetaMP: Metalearning-Based Multipatch Image Aesthetics Assessment","display_name":"MetaMP: Metalearning-Based Multipatch Image Aesthetics Assessment","publication_year":2022,"publication_date":"2022-05-17","ids":{"openalex":"https://openalex.org/W4280563717","doi":"https://doi.org/10.1109/tcyb.2022.3169017","pmid":"https://pubmed.ncbi.nlm.nih.gov/35580097"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2022.3169017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3169017","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066144350","display_name":"Jiachen Yang","orcid":"https://orcid.org/0000-0003-2558-552X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiachen Yang","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081231809","display_name":"Yanshuang Zhou","orcid":"https://orcid.org/0000-0002-0490-0474"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanshuang Zhou","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056718303","display_name":"Yang Zhao","orcid":"https://orcid.org/0000-0001-5252-658X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Zhao","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059540876","display_name":"Wen Lu","orcid":"https://orcid.org/0000-0002-8193-6016"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Lu","raw_affiliation_strings":["School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101785348","display_name":"Xinbo Gao","orcid":"https://orcid.org/0000-0003-1443-0776"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinbo Gao","raw_affiliation_strings":["State Key Laboratory of Integrated Services Networks, School of Electronic Engineering, Xidian University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Services Networks, School of Electronic Engineering, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5066144350"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":1.8339,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.86423465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"53","issue":"9","first_page":"5716","last_page":"5728"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9977999925613403,"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/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6558374762535095},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.6513362526893616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5757384896278381},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4992685317993164},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4389890432357788},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37999653816223145},{"id":"https://openalex.org/keywords/aesthetics","display_name":"Aesthetics","score":0.35498425364494324},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.12064525485038757}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6558374762535095},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.6513362526893616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5757384896278381},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4992685317993164},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4389890432357788},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37999653816223145},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"score":0.35498425364494324},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.12064525485038757},{"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2022.3169017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2022.3169017","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Cybernetics","raw_type":"journal-article"},{"id":"pmid:35580097","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35580097","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4099999964237213,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G8191841786","display_name":null,"funder_award_id":"61871283","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/W36434594","https://openalex.org/W172260869","https://openalex.org/W1511924373","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1896080482","https://openalex.org/W1938565953","https://openalex.org/W1971014006","https://openalex.org/W1972226007","https://openalex.org/W1976414467","https://openalex.org/W1997095443","https://openalex.org/W2063948594","https://openalex.org/W2078807908","https://openalex.org/W2080754665","https://openalex.org/W2158698691","https://openalex.org/W2165698076","https://openalex.org/W2170658603","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2217895792","https://openalex.org/W2514622527","https://openalex.org/W2526152041","https://openalex.org/W2604528050","https://openalex.org/W2604763608","https://openalex.org/W2754213847","https://openalex.org/W2775740880","https://openalex.org/W2779483295","https://openalex.org/W2786768213","https://openalex.org/W2888728157","https://openalex.org/W2897926040","https://openalex.org/W2909912710","https://openalex.org/W2911235000","https://openalex.org/W2931027027","https://openalex.org/W2962858109","https://openalex.org/W2965006338","https://openalex.org/W2966486655","https://openalex.org/W2969536649","https://openalex.org/W2970253846","https://openalex.org/W2979509742","https://openalex.org/W2997513180","https://openalex.org/W3003957020","https://openalex.org/W3015585292","https://openalex.org/W3016197248","https://openalex.org/W3034776788","https://openalex.org/W3091617927","https://openalex.org/W3093270589","https://openalex.org/W3094277917","https://openalex.org/W3098688893","https://openalex.org/W3103635814","https://openalex.org/W3121625413","https://openalex.org/W3138129477","https://openalex.org/W3163842339","https://openalex.org/W3174134652","https://openalex.org/W3175164844","https://openalex.org/W3194672963","https://openalex.org/W3209710747","https://openalex.org/W4294646197","https://openalex.org/W4297775537","https://openalex.org/W6601502966","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6649928981","https://openalex.org/W6685083886","https://openalex.org/W6736057607","https://openalex.org/W6737664043","https://openalex.org/W6750254146","https://openalex.org/W6766597972","https://openalex.org/W6784326800","https://openalex.org/W6786740612","https://openalex.org/W6797548016"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W3095877357","https://openalex.org/W183202219","https://openalex.org/W10861731","https://openalex.org/W2072565696","https://openalex.org/W4386821099"],"abstract_inverted_index":{"Image":[0],"aesthetics":[1,11],"assessment":[2,148],"(IAA)":[3],"is":[4,72],"a":[5,57,86,92],"subjective":[6],"and":[7,19,91],"complex":[8],"task.":[9],"The":[10,70],"of":[12,110,132,138,158],"different":[13],"themes":[14],"vary":[15],"greatly":[16],"in":[17,25,114],"content":[18],"aesthetic":[20,28,33,80,122],"results,":[21],"whether":[22],"they":[23],"are":[24],"the":[26,36,98,102,108,111,117,130,133,136],"same":[27],"community":[29],"or":[30],"not.":[31],"In":[32,82,128],"evaluation":[34,131],"tasks,":[35],"pretrained":[37],"network":[38,71,95,156],"with":[39,116],"direct":[40],"fine-tune":[41],"may":[42],"not":[43,144],"be":[44],"able":[45],"to":[46,49,63,65,77,96],"quickly":[47],"adapt":[48,64],"tasks":[50,68],"on":[51,75,121],"various":[52,66],"themes.":[53],"This":[54],"article":[55],"introduces":[56],"metalearning-based":[58],"multipatch":[59,93],"(MetaMP)":[60],"IAA":[61],"method":[62,113],"thematic":[67],"quickly.":[69],"trained":[73],"based":[74,120],"metalearning":[76,140],"obtain":[78],"content-oriented":[79],"expression.":[81],"addition,":[83,129],"we":[84],"design":[85],"complete-information":[87],"patch":[88],"selection":[89],"scheme":[90],"(MP)":[94],"make":[97],"fine":[99],"details":[100],"fit":[101],"overall":[103],"impression.":[104],"Experimental":[105],"results":[106],"demonstrate":[107],"superiority":[109],"proposed":[112],"comparison":[115],"state-of-the-art":[118],"models":[119],"visual":[123],"analysis":[124],"(AVA)":[125],"benchmark":[126],"datasets.":[127],"dataset":[134],"shows":[135],"effectiveness":[137],"our":[139],"training":[141],"model,":[142],"which":[143],"only":[145],"improves":[146],"MetaMP":[147],"accuracy":[149],"but":[150],"also":[151],"provides":[152],"valuable":[153],"guidance":[154],"for":[155],"initialization":[157],"IAA.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
