{"id":"https://openalex.org/W2963529609","doi":"https://doi.org/10.24963/ijcai.2018/97","title":"Enhanced-alignment Measure for Binary Foreground Map Evaluation","display_name":"Enhanced-alignment Measure for Binary Foreground Map Evaluation","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2963529609","doi":"https://doi.org/10.24963/ijcai.2018/97","mag":"2963529609"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/97","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/97","pdf_url":"https://www.ijcai.org/proceedings/2018/0097.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0097.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056294284","display_name":"Deng-Ping Fan","orcid":"https://orcid.org/0000-0002-5245-7518"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Deng-Ping Fan","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101949507","display_name":"Cheng Gong","orcid":"https://orcid.org/0000-0002-6594-8375"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Gong","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004299336","display_name":"Yang Cao","orcid":"https://orcid.org/0000-0002-2891-4379"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Cao","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035195328","display_name":"Bo Ren","orcid":"https://orcid.org/0000-0001-8179-9122"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Ren","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037131575","display_name":"Ming\u2010Ming Cheng","orcid":"https://orcid.org/0000-0001-5550-8758"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Ming Cheng","raw_affiliation_strings":["College of Computer and Control Engineering, Nankai University"],"affiliations":[{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068743986","display_name":"Ali Borji","orcid":"https://orcid.org/0000-0001-8198-0335"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]},{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Ali Borji","raw_affiliation_strings":["Center for Research in Computer Vision, Central Florida University","College of Computer and Control Engineering, Nankai University"],"affiliations":[{"raw_affiliation_string":"Center for Research in Computer Vision, Central Florida University","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"College of Computer and Control Engineering, Nankai University","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5056294284"],"corresponding_institution_ids":["https://openalex.org/I205237279"],"apc_list":null,"apc_paid":null,"fwci":33.1489,"has_fulltext":false,"cited_by_count":1464,"citation_normalized_percentile":{"value":0.99741132,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"698","last_page":"704"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9984999895095825,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9829000234603882,"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/pixel","display_name":"Pixel","score":0.7459080219268799},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.7243595123291016},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7190134525299072},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6890896558761597},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6146515607833862},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5273897051811218},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.5106104016304016},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.49100664258003235},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.464147686958313},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4546048045158386},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45144906640052795},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.44111737608909607},{"id":"https://openalex.org/keywords/binary-data","display_name":"Binary data","score":0.4358679950237274},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41488707065582275},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2740376591682434},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24831998348236084},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.18832120299339294}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7459080219268799},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.7243595123291016},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7190134525299072},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6890896558761597},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6146515607833862},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5273897051811218},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.5106104016304016},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.49100664258003235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.464147686958313},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4546048045158386},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45144906640052795},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44111737608909607},{"id":"https://openalex.org/C2779190172","wikidata":"https://www.wikidata.org/wiki/Q4913888","display_name":"Binary data","level":3,"score":0.4358679950237274},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41488707065582275},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2740376591682434},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24831998348236084},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.18832120299339294},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.24963/ijcai.2018/97","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/97","pdf_url":"https://www.ijcai.org/proceedings/2018/0097.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:stars.library.ucf.edu:scopus2015-11532","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2015/10533","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2015-2019","raw_type":"text"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/97","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/97","pdf_url":"https://www.ijcai.org/proceedings/2018/0097.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G693123427","display_name":null,"funder_award_id":"61572264","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7156112097","display_name":null,"funder_award_id":"61620106008","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":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2963529609.pdf","grobid_xml":"https://content.openalex.org/works/W2963529609.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1613438798","https://openalex.org/W1785730614","https://openalex.org/W1894057436","https://openalex.org/W1942214758","https://openalex.org/W1994922096","https://openalex.org/W1996326832","https://openalex.org/W2014930414","https://openalex.org/W2031489346","https://openalex.org/W2036973297","https://openalex.org/W2086791339","https://openalex.org/W2091695913","https://openalex.org/W2094053047","https://openalex.org/W2100470808","https://openalex.org/W2110158442","https://openalex.org/W2116719896","https://openalex.org/W2117301471","https://openalex.org/W2121927366","https://openalex.org/W2128340050","https://openalex.org/W2131650023","https://openalex.org/W2133665775","https://openalex.org/W2159772167","https://openalex.org/W2171378720","https://openalex.org/W2270657321","https://openalex.org/W2293332611","https://openalex.org/W2338972621","https://openalex.org/W2461475918","https://openalex.org/W2519528544","https://openalex.org/W2569272946","https://openalex.org/W2963868681","https://openalex.org/W3104979525","https://openalex.org/W3125520697","https://openalex.org/W4239147634"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4308259661","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4328132048","https://openalex.org/W1969901537","https://openalex.org/W2119768059"],"abstract_inverted_index":{"The":[0],"existing":[1],"binary":[2,58],"foreground":[3],"map":[4],"(FM)":[5],"measures":[6,19,61,104],"address":[7],"various":[8],"types":[9],"of":[10,98,143],"errors":[11],"in":[12,46,82,134,141],"either":[13],"pixel-wise":[14],"or":[15,23],"structural":[16],"ways.":[17],"These":[18],"consider":[20],"pixel-level":[21],"match":[22],"image-level":[24,79,87],"information":[25,42],"independently,":[26],"while":[27],"cognitive":[28],"vision":[29,35],"studies":[30],"have":[31],"shown":[32],"that":[33],"human":[34,128],"is":[36],"highly":[37],"sensitive":[38],"to":[39,152],"both":[40],"global":[41],"and":[43,62,66,89],"local":[44,74,90],"details":[45],"scenes.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51,146],"take":[52],"a":[53,64],"detailed":[54],"look":[55],"at":[56],"current":[57],"FM":[59],"evaluation":[60],"propose":[63],"novel":[65],"effective":[67],"E-measure":[68],"(Enhanced-alignment":[69],"measure).":[70],"Our":[71],"measure":[72,100],"combines":[73],"pixel":[75,91],"values":[76],"with":[77,155],"the":[78,96,102,137],"mean":[80],"value":[81],"one":[83],"term,":[84],"jointly":[85],"capturing":[86],"statistics":[88],"matching":[92],"information.":[93],"We":[94,130],"demonstrate":[95],"superiority":[97],"our":[99],"over":[101],"available":[103],"on":[105],"4":[106],"popular":[107,157],"datasets":[108],"via":[109],"5":[110],"meta-measures,":[111],"including":[112],"ranking":[113],"models":[114],"for":[115],"applications,":[116],"demoting":[117],"generic,":[118],"random":[119],"Gaussian":[120],"noise":[121],"maps,":[122],"ground-truth":[123],"switch,":[124],"as":[125,127],"well":[126],"judgments.":[129],"find":[131],"large":[132],"improvements":[133],"almost":[135],"all":[136],"meta-measures.":[138],"For":[139],"instance,":[140],"terms":[142],"application":[144],"ranking,":[145],"observe":[147],"improvement":[148],"ranging":[149],"from":[150],"9.08%":[151],"19.65%":[153],"compared":[154],"other":[156],"measures.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":56},{"year":2025,"cited_by_count":302},{"year":2024,"cited_by_count":322},{"year":2023,"cited_by_count":254},{"year":2022,"cited_by_count":218},{"year":2021,"cited_by_count":168},{"year":2020,"cited_by_count":106},{"year":2019,"cited_by_count":34},{"year":2018,"cited_by_count":4}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
