{"id":"https://openalex.org/W2293846591","doi":"https://doi.org/10.1109/icip.2015.7351067","title":"Visual aesthetic quality assessment with a regression model","display_name":"Visual aesthetic quality assessment with a regression model","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2293846591","doi":"https://doi.org/10.1109/icip.2015.7351067","mag":"2293846591"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7351067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"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/A5087450299","display_name":"Yueying Kao","orcid":"https://orcid.org/0000-0002-5796-7541"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueying Kao","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100329478","display_name":"Chong Wang","orcid":"https://orcid.org/0009-0008-5190-7792"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chong Wang","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028693655","display_name":"Kaiqi Huang","orcid":"https://orcid.org/0000-0002-2677-9273"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiqi Huang","raw_affiliation_strings":["Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center for Research on Intelligent Perception and Computing, National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19820366"],"apc_list":null,"apc_paid":null,"fwci":3.1088,"has_fulltext":false,"cited_by_count":83,"citation_normalized_percentile":{"value":0.95917114,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1583","last_page":"1587"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9987000226974487,"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":0.9987000226974487,"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":0.9954000115394592,"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"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9922999739646912,"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/computer-science","display_name":"Computer science","score":0.7336417436599731},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7009835243225098},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6639583706855774},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6507848501205444},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.6023918986320496},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5866379737854004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5679047703742981},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5311663746833801},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45681795477867126},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16172346472740173},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.139873206615448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7336417436599731},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7009835243225098},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6639583706855774},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6507848501205444},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.6023918986320496},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5866379737854004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5679047703742981},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5311663746833801},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45681795477867126},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16172346472740173},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.139873206615448},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7351067","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7351067","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W318792885","https://openalex.org/W1511924373","https://openalex.org/W1566135517","https://openalex.org/W1606858007","https://openalex.org/W1625255723","https://openalex.org/W1849277567","https://openalex.org/W1969923256","https://openalex.org/W1985560945","https://openalex.org/W1997095443","https://openalex.org/W2021820150","https://openalex.org/W2048835603","https://openalex.org/W2052943004","https://openalex.org/W2056380823","https://openalex.org/W2063948594","https://openalex.org/W2078807908","https://openalex.org/W2080754665","https://openalex.org/W2104915826","https://openalex.org/W2131846894","https://openalex.org/W2147238549","https://openalex.org/W2153635508","https://openalex.org/W2157922518","https://openalex.org/W2160278098","https://openalex.org/W2160440850","https://openalex.org/W2163605009","https://openalex.org/W2170658603","https://openalex.org/W6611089629","https://openalex.org/W6630520941","https://openalex.org/W6636412649","https://openalex.org/W6636494156","https://openalex.org/W6639204139","https://openalex.org/W6649928981","https://openalex.org/W6675445837","https://openalex.org/W6683388899","https://openalex.org/W6683866063","https://openalex.org/W6684191040","https://openalex.org/W6685083886"],"related_works":["https://openalex.org/W4287776258","https://openalex.org/W3027997911","https://openalex.org/W3021430260","https://openalex.org/W1970158984","https://openalex.org/W2359645249","https://openalex.org/W2072034916","https://openalex.org/W2012241321","https://openalex.org/W2007205149","https://openalex.org/W3176894857","https://openalex.org/W2391037776"],"abstract_inverted_index":{"Aesthetic":[0],"image":[1],"analysis":[2],"has":[3],"drawn":[4],"much":[5],"attention":[6],"in":[7,95],"recent":[8],"years.":[9],"However,":[10],"assessing":[11],"the":[12,53,64,69,79,99,117,122,135],"aesthetic":[13,16,28,54,80,90,105,125],"quality":[14,29,126],"especially":[15],"score":[17],"prediction":[18],"is":[19,75],"a":[20,32,37,43,47,72,110],"challenging":[21],"problem.":[22],"In":[23],"this":[24],"paper,":[25],"we":[26,62],"interpret":[27],"assessment":[30],"as":[31],"regression":[33,44,73,100],"problem":[34],"and":[35,133],"present":[36],"new":[38],"framework":[39],"by":[40],"directly":[41],"training":[42],"model":[45,74,101],"using":[46],"neural":[48],"network.":[49],"Firstly,":[50],"to":[51,59,67,128],"extract":[52],"features":[55],"which":[56,86],"are":[57],"difficult":[58],"design":[60],"manually,":[61],"utilize":[63],"convolutional":[65],"network":[66],"learn":[68],"features.":[70,81],"Then,":[71],"trained":[76],"based":[77],"on":[78,109],"Different":[82],"from":[83],"classification":[84],"models":[85],"can":[87,102,120],"only":[88],"predict":[89,103],"class":[91],"(high":[92],"or":[93],"low)":[94],"most":[96],"existing":[97],"works,":[98],"continuous":[104],"score.":[106],"Experimental":[107],"results":[108],"recently":[111],"published":[112],"large-scale":[113],"dataset":[114],"show":[115],"that":[116],"proposed":[118],"method":[119],"assess":[121],"degree":[123],"of":[124],"similar":[127],"human":[129],"visual":[130],"system":[131],"effectively":[132],"outperforms":[134],"state-of-the-art":[136],"methods.":[137]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":11},{"year":2016,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
