{"id":"https://openalex.org/W2972287851","doi":"https://doi.org/10.1109/access.2019.2939681","title":"Predicting Image Emotion Distribution by Learning Labels\u2019 Correlation","display_name":"Predicting Image Emotion Distribution by Learning Labels\u2019 Correlation","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2972287851","doi":"https://doi.org/10.1109/access.2019.2939681","mag":"2972287851"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2939681","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2939681","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08825846.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08825846.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015995416","display_name":"Yangyu Fan","orcid":"https://orcid.org/0000-0003-0689-5418"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yangyu Fan","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hansen Yang","orcid":"https://orcid.org/0000-0001-6723-9663"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hansen Yang","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","ORCiD","School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-6723-9663","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"ORCiD","institution_ids":[]},{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025371735","display_name":"Zuhe Li","orcid":"https://orcid.org/0000-0002-2511-3226"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zuhe Li","raw_affiliation_strings":["School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064499660","display_name":"Shu Liu","orcid":"https://orcid.org/0000-0002-2903-9270"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Liu","raw_affiliation_strings":["School of Computer Science and Engineering, Central South University, Changsha, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7049,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.78140567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"129997","last_page":"130007"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.988099992275238,"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":0.7156489491462708},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6709679961204529},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6086212992668152},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5682742595672607},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5298148393630981},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49443936347961426},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4793458878993988},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4790874123573303},{"id":"https://openalex.org/keywords/emotion-classification","display_name":"Emotion classification","score":0.45458874106407166},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3452044129371643},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19460567831993103},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.16884812712669373}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7156489491462708},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6709679961204529},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6086212992668152},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5682742595672607},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5298148393630981},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49443936347961426},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4793458878993988},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4790874123573303},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.45458874106407166},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3452044129371643},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19460567831993103},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.16884812712669373},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2939681","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2939681","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08825846.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5b3421e93ab34f5fb62b8134ec0688f3","is_oa":true,"landing_page_url":"https://doaj.org/article/5b3421e93ab34f5fb62b8134ec0688f3","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":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 129997-130007 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2939681","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2939681","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08825846.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.699999988079071}],"awards":[{"id":"https://openalex.org/G5083996272","display_name":null,"funder_award_id":"2019JJ50808","funder_id":"https://openalex.org/F4320322843","funder_display_name":"Natural Science Foundation of\u00a0Hunan Province"},{"id":"https://openalex.org/G7188042083","display_name":null,"funder_award_id":"61902435","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8630332848","display_name":null,"funder_award_id":"61702462","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"},{"id":"https://openalex.org/F4320322843","display_name":"Natural Science Foundation of\u00a0Hunan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W195533127","https://openalex.org/W1529085430","https://openalex.org/W1686810756","https://openalex.org/W1903029394","https://openalex.org/W1950412479","https://openalex.org/W1965343349","https://openalex.org/W1995903905","https://openalex.org/W2003856922","https://openalex.org/W2014713986","https://openalex.org/W2031248101","https://openalex.org/W2056553798","https://openalex.org/W2066454034","https://openalex.org/W2075456404","https://openalex.org/W2089468765","https://openalex.org/W2105842272","https://openalex.org/W2108394867","https://openalex.org/W2110700950","https://openalex.org/W2137226992","https://openalex.org/W2146241755","https://openalex.org/W2163605009","https://openalex.org/W2166122509","https://openalex.org/W2166267120","https://openalex.org/W2295328086","https://openalex.org/W2318149822","https://openalex.org/W2330485005","https://openalex.org/W2347880541","https://openalex.org/W2429914308","https://openalex.org/W2488154566","https://openalex.org/W2513550067","https://openalex.org/W2515036155","https://openalex.org/W2517991028","https://openalex.org/W2570829410","https://openalex.org/W2577763257","https://openalex.org/W2811296027","https://openalex.org/W2908347420","https://openalex.org/W2951589678","https://openalex.org/W2963042261","https://openalex.org/W2963992782","https://openalex.org/W2964167669","https://openalex.org/W3022720450","https://openalex.org/W6607976765","https://openalex.org/W6631767438","https://openalex.org/W6637373629","https://openalex.org/W6675783020","https://openalex.org/W6680532697","https://openalex.org/W6684191040","https://openalex.org/W6684808098","https://openalex.org/W6691937106","https://openalex.org/W6705060728","https://openalex.org/W6730410798"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2323648130","https://openalex.org/W2157140558","https://openalex.org/W2378782423","https://openalex.org/W2388988621","https://openalex.org/W2357797405","https://openalex.org/W2366623913","https://openalex.org/W2374905595","https://openalex.org/W2516693588","https://openalex.org/W2116112408"],"abstract_inverted_index":{"Image":[0],"emotion":[1,33,98,139],"analysis":[2,94],"attracts":[3],"considerable":[4],"attention":[5],"with":[6,45,67,120,155],"the":[7,71,88,95,117,123,149,153,156,170],"increasing":[8],"demanding":[9],"of":[10,43,81,91,158,172],"opinion":[11],"mining":[12],"in":[13,56],"social":[14],"networks.":[15],"Emotion":[16],"evoked":[17],"by":[18],"an":[19,49],"image":[20,32,138],"is":[21],"always":[22],"ambiguous":[23],"for":[24],"emotion's":[25],"subjectivity.":[26],"Different":[27],"from":[28,114,152],"previous":[29],"researches":[30],"on":[31,106,164],"classification,":[34],"Label":[35],"Distribution":[36],"Learning":[37,108],"framework":[38],"which":[39,110],"assigns":[40],"a":[41,103,112,144],"set":[42],"labels":[44,63,72,99,119],"degree":[46],"value":[47],"to":[48,87,116,132,147],"instance,":[50],"describes":[51],"emotions":[52],"more":[53],"explicitly.":[54],"However,":[55],"our":[57,173],"study,":[58],"we":[59,93,142],"find":[60],"that":[61,135],"some":[62,75,129],"have":[64],"co-occurrence":[65],"relation":[66],"others":[68],"and":[69,100],"all":[70],"together":[73],"appear":[74],"structural":[76],"forms.":[77],"To":[78],"make":[79],"use":[80],"these":[82],"relations":[83],"as":[84],"complementary":[85],"information":[86],"holistic":[89],"distribution":[90,118],"labels,":[92],"correlations":[96],"among":[97],"then":[101],"propose":[102,143],"method":[104,146],"based":[105],"Structural":[107],"framework,":[109],"learns":[111],"mapping":[113],"images":[115,126,154],"correlations.":[121],"On":[122],"other":[124],"hand,":[125],"usually":[127],"contain":[128],"emotion-unrelated":[130],"contents,":[131],"extract":[133],"features":[134],"can":[136],"represent":[137],"at":[140],"utmost,":[141],"cropping":[145],"select":[148],"emotional":[150],"region":[151],"help":[157],"Fully":[159],"Convolutional":[160],"Networks.":[161],"Extensive":[162],"experiments":[163],"two":[165],"widely":[166],"used":[167],"datasets":[168],"show":[169],"advantages":[171],"methods.":[174]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
