{"id":"https://openalex.org/W2576764453","doi":"https://doi.org/10.1109/lsp.2017.2654803","title":"Combining Convolutional and Recurrent Neural Networks for Human Skin Detection","display_name":"Combining Convolutional and Recurrent Neural Networks for Human Skin Detection","publication_year":2017,"publication_date":"2017-01-17","ids":{"openalex":"https://openalex.org/W2576764453","doi":"https://doi.org/10.1109/lsp.2017.2654803","mag":"2576764453"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2017.2654803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2654803","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","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/A5009511406","display_name":"Haiqiang Zuo","orcid":"https://orcid.org/0000-0003-3790-7004"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]},{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Haiqiang Zuo","raw_affiliation_strings":["Department of Chemical Equipment and Control Engineering, China University of Petroleum, Qingdao, China","Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Chemical Equipment and Control Engineering, China University of Petroleum, Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]},{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047220188","display_name":"Heng Fan","orcid":"https://orcid.org/0000-0002-7033-3690"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heng Fan","raw_affiliation_strings":["Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023894377","display_name":"Erik Blasch","orcid":"https://orcid.org/0000-0001-6894-6108"},"institutions":[{"id":"https://openalex.org/I1280414376","display_name":"United States Air Force Research Laboratory","ror":"https://ror.org/02e2egq70","country_code":"US","type":"facility","lineage":["https://openalex.org/I1280414376","https://openalex.org/I1330347796","https://openalex.org/I4210102105","https://openalex.org/I4389425425"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erik Blasch","raw_affiliation_strings":["Air Force Research Laboratory, Rome, NY, USA"],"affiliations":[{"raw_affiliation_string":"Air Force Research Laboratory, Rome, NY, USA","institution_ids":["https://openalex.org/I1280414376"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061469520","display_name":"Haibin Ling","orcid":"https://orcid.org/0000-0003-4094-8413"},"institutions":[{"id":"https://openalex.org/I84392919","display_name":"Temple University","ror":"https://ror.org/00kx1jb78","country_code":"US","type":"education","lineage":["https://openalex.org/I84392919"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibin Ling","raw_affiliation_strings":["Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I84392919"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009511406"],"corresponding_institution_ids":["https://openalex.org/I4210162190","https://openalex.org/I84392919"],"apc_list":null,"apc_paid":null,"fwci":5.8177,"has_fulltext":false,"cited_by_count":125,"citation_normalized_percentile":{"value":0.97614435,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"24","issue":"3","first_page":"289","last_page":"293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.992900013923645,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.992900013923645,"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/T10392","display_name":"Cutaneous Melanoma Detection and Management","score":0.9466000199317932,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9449999928474426,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8377823233604431},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8005527257919312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7482260465621948},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.6661524176597595},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6390946507453918},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.586376428604126},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5857312083244324},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5720624327659607},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5649000406265259},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.5297492742538452},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.44531822204589844},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3934769630432129},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.34524476528167725}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8377823233604431},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8005527257919312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7482260465621948},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.6661524176597595},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6390946507453918},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.586376428604126},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5857312083244324},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5720624327659607},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5649000406265259},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.5297492742538452},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.44531822204589844},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3934769630432129},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34524476528167725},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2017.2654803","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2017.2654803","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3160831190","display_name":null,"funder_award_id":"61528204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G399210199","display_name":null,"funder_award_id":"13505210","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4728448454","display_name":null,"funder_award_id":"1449860","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6263506401","display_name":null,"funder_award_id":"61103056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W196214544","https://openalex.org/W341125965","https://openalex.org/W1185138977","https://openalex.org/W1546771929","https://openalex.org/W1578204867","https://openalex.org/W1745334888","https://openalex.org/W1903029394","https://openalex.org/W1905882502","https://openalex.org/W1909234690","https://openalex.org/W1910657905","https://openalex.org/W1923697677","https://openalex.org/W1963882359","https://openalex.org/W1977995219","https://openalex.org/W1986384291","https://openalex.org/W1990248972","https://openalex.org/W2000488160","https://openalex.org/W2022508996","https://openalex.org/W2041649634","https://openalex.org/W2043200866","https://openalex.org/W2058905763","https://openalex.org/W2070692575","https://openalex.org/W2073105997","https://openalex.org/W2089824010","https://openalex.org/W2091313930","https://openalex.org/W2104960492","https://openalex.org/W2124592697","https://openalex.org/W2125448563","https://openalex.org/W2132565621","https://openalex.org/W2150809766","https://openalex.org/W2153746365","https://openalex.org/W2183022875","https://openalex.org/W2204696980","https://openalex.org/W2227603301","https://openalex.org/W2257307118","https://openalex.org/W2264695561","https://openalex.org/W2267126114","https://openalex.org/W2288122362","https://openalex.org/W2395758897","https://openalex.org/W2403483107","https://openalex.org/W2437797956","https://openalex.org/W2618530766","https://openalex.org/W2953318193","https://openalex.org/W2963166928","https://openalex.org/W2963881378","https://openalex.org/W2964006742","https://openalex.org/W4285719527","https://openalex.org/W6607974698","https://openalex.org/W6627828623","https://openalex.org/W6632360823","https://openalex.org/W6634858844","https://openalex.org/W6639780620","https://openalex.org/W6692936304","https://openalex.org/W6712049592"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Skin":[0],"detection":[1,57,82,191],"from":[2],"images,":[3],"typically":[4],"used":[5],"as":[6,17,36],"a":[7,11,28,65],"preprocessing":[8],"step,":[9],"has":[10],"wide":[12],"range":[13],"of":[14,178,189],"applications":[15],"such":[16,35],"dermatology":[18],"diagnostics,":[19],"human":[20,145],"computer":[21],"interaction":[22],"designs,":[23],"and":[24,43,50,119,139,171],"etc.":[25],"It":[26,59],"is":[27,60,68],"challenging":[29],"problem":[30],"due":[31],"to":[32,55,62],"many":[33],"factors":[34],"variation":[37],"in":[38,45,103,164,192],"pigment":[39],"melanin,":[40],"uneven":[41],"illumination,":[42],"differences":[44],"ethnicity":[46],"geographics.":[47],"Besides,":[48],"age":[49],"gender":[51],"introduce":[52],"additional":[53],"difficulties":[54],"the":[56,74,115,133,160,169,176,179,186],"process.":[58],"hard":[61],"determine":[63],"whether":[64],"single":[66],"pixel":[67],"skin":[69,80,146,173,190],"or":[70],"nonskin":[71],"without":[72],"considering":[73],"context.":[75],"An":[76],"efficient":[77],"traditional":[78],"hand-engineered":[79],"color":[81],"algorithm":[83],"requires":[84],"extensive":[85],"work":[86],"by":[87],"domain":[88],"experts.":[89],"Recently,":[90],"deep":[91],"learning":[92],"algorithms,":[93],"especially":[94],"convolutional":[95,135],"neural":[96,128,136],"networks":[97,129,137],"(CNNs),":[98],"have":[99],"achieved":[100],"great":[101],"success":[102],"pixel-wise":[104],"labeling":[105],"tasks.":[106],"However,":[107],"CNN-based":[108],"architectures":[109],"are":[110],"not":[111],"sufficient":[112],"for":[113,144],"modeling":[114],"relationship":[116],"between":[117],"pixels":[118],"their":[120],"neighbors.":[121],"In":[122,148],"this":[123],"letter,":[124],"we":[125],"integrate":[126],"recurrent":[127],"(RNNs)":[130],"layers":[131,151,158,184],"into":[132],"fully":[134],"(FCNs),":[138],"develop":[140],"an":[141],"end-to-end":[142],"network":[143],"detection.":[147],"particular,":[149],"FCN":[150],"capture":[152],"generic":[153],"local":[154],"features,":[155],"while":[156],"RNN":[157,183],"model":[159],"semantic":[161],"contextual":[162],"dependencies":[163],"images.":[165],"Experimental":[166],"results":[167],"on":[168],"COMPAQ":[170],"ECU":[172],"datasets":[174],"validate":[175],"effectiveness":[177],"proposed":[180],"approach,":[181],"where":[182],"enhance":[185],"discriminative":[187],"power":[188],"complex":[193],"background":[194],"situations.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":18},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":30},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
