{"id":"https://openalex.org/W2903331744","doi":"https://doi.org/10.1109/access.2018.2884969","title":"Deep Hierarchical Network With Line Segment Learning for Quantitative Analysis of Facial Palsy","display_name":"Deep Hierarchical Network With Line Segment Learning for Quantitative Analysis of Facial Palsy","publication_year":2018,"publication_date":"2018-12-04","ids":{"openalex":"https://openalex.org/W2903331744","doi":"https://doi.org/10.1109/access.2018.2884969","mag":"2903331744"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2884969","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2884969","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08558494.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":null,"license_id":null,"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/ielx7/6287639/8600701/08558494.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015206948","display_name":"Gee-Sern Hsu","orcid":"https://orcid.org/0000-0003-2631-0448"},"institutions":[{"id":"https://openalex.org/I47519274","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94","country_code":"TW","type":"education","lineage":["https://openalex.org/I47519274"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Gee-Sern Jison Hsu","raw_affiliation_strings":["Taipei Medical University, Taipei, TW"],"raw_orcid":"https://orcid.org/0000-0003-2631-0448","affiliations":[{"raw_affiliation_string":"Taipei Medical University, Taipei, TW","institution_ids":["https://openalex.org/I47519274"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081547615","display_name":"Jiunn\u2010Horng Kang","orcid":"https://orcid.org/0000-0002-7850-4140"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jiunn-Horng Kang","raw_affiliation_strings":["National Taiwan University of Science and Technology, Taipei, TW"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology, Taipei, TW","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087166395","display_name":"Wen-Fong Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Fong Huang","raw_affiliation_strings":["Artificial Vision Laboratory, National Taiwan University of Science and Technology, Taipei, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Vision Laboratory, National Taiwan University of Science and Technology, Taipei, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"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":1.5224,"has_fulltext":true,"cited_by_count":53,"citation_normalized_percentile":{"value":0.82599365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"4833","last_page":"4842"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12301","display_name":"Facial Nerve Paralysis Treatment and Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12301","display_name":"Facial Nerve Paralysis Treatment and Research","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"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/T11448","display_name":"Face recognition and analysis","score":0.9987999796867371,"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/T11322","display_name":"Facial Rejuvenation and Surgery Techniques","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2708","display_name":"Dermatology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7352707386016846},{"id":"https://openalex.org/keywords/palsy","display_name":"Palsy","score":0.667969286441803},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5633301138877869},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.43851280212402344},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4353369474411011},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3652030825614929},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3430732488632202},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.1504077911376953},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07976245880126953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7352707386016846},{"id":"https://openalex.org/C2778097013","wikidata":"https://www.wikidata.org/wiki/Q68212673","display_name":"Palsy","level":3,"score":0.667969286441803},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5633301138877869},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.43851280212402344},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4353369474411011},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3652030825614929},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3430732488632202},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.1504077911376953},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07976245880126953},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C204787440","wikidata":"https://www.wikidata.org/wiki/Q188504","display_name":"Alternative medicine","level":2,"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.2018.2884969","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2884969","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08558494.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:56f84042435b4d51a2d2b880942eb3f0","is_oa":true,"landing_page_url":"https://doaj.org/article/56f84042435b4d51a2d2b880942eb3f0","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 4833-4842 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2884969","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2884969","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08558494.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4541003122","display_name":null,"funder_award_id":"MOST 106-2221-E-011-144","funder_id":"https://openalex.org/F4320309618","funder_display_name":"Ministry of Science and Technology"},{"id":"https://openalex.org/G8920540342","display_name":null,"funder_award_id":"106-TMU-NTUST-106-05","funder_id":"https://openalex.org/F4320324515","funder_display_name":"National Taiwan University of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"},{"id":"https://openalex.org/F4320322814","display_name":"Taipei Medical University","ror":"https://ror.org/05031qk94"},{"id":"https://openalex.org/F4320323900","display_name":"National Taiwan University","ror":"https://ror.org/05bqach95"},{"id":"https://openalex.org/F4320324515","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2903331744.pdf","grobid_xml":"https://content.openalex.org/works/W2903331744.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W13529951","https://openalex.org/W124653583","https://openalex.org/W165395649","https://openalex.org/W639708223","https://openalex.org/W1835934842","https://openalex.org/W1849007038","https://openalex.org/W1990937109","https://openalex.org/W1998294030","https://openalex.org/W2058961190","https://openalex.org/W2111372597","https://openalex.org/W2121684305","https://openalex.org/W2133747057","https://openalex.org/W2157285372","https://openalex.org/W2215581249","https://openalex.org/W2284800790","https://openalex.org/W2295693344","https://openalex.org/W2325939864","https://openalex.org/W2570343428","https://openalex.org/W2609869850","https://openalex.org/W2746753454","https://openalex.org/W2787491164","https://openalex.org/W2893321012","https://openalex.org/W2949662773","https://openalex.org/W2963566548","https://openalex.org/W2964014798","https://openalex.org/W3104792420","https://openalex.org/W3106250896","https://openalex.org/W4241071816","https://openalex.org/W6604957760","https://openalex.org/W6620707391","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W2372463024","https://openalex.org/W4383066092","https://openalex.org/W4234496484","https://openalex.org/W3215138031"],"abstract_inverted_index":{"We":[0,313],"propose":[1],"the":[2,8,22,33,39,53,62,74,80,95,98,101,104,111,115,118,129,152,170,175,179,184,195,204,209,212,217,227,231,238,241,246,255,259,271,297,305,311,316,323,330,333,340,344,350],"deep":[3],"hierarchical":[4],"network":[5,125,135,141,149,161,168],"(DHN)":[6],"for":[7,61,79,150,202,216,360],"quantitative":[9,82,228,341],"analysis":[10,83],"of":[11,26,35,55,65,84,91,190,197,211,219,230,240,254,273,284,332,343],"facial":[12,27,41,46,49,66,85,105,153,205,220,232,300,307,334,361],"palsy.":[13,86],"Facial":[14,248],"palsy,":[15,20],"also":[16,328],"known":[17],"as":[18],"Bell\u2019s":[19],"is":[21,126,136,162],"most":[23],"common":[24],"type":[25],"nerve":[28],"palsy":[29,67,120,224,233,325,335,362],"that":[30,143,173,261,315,349],"results":[31],"in":[32,38,310],"loss":[34],"muscle":[36],"control":[37],"affected":[40],"regions.":[42,121],"Typical":[43],"symptoms":[44],"include":[45,304],"deformity":[47],"and":[48,107,114,155,178,222,236,290,356],"expression":[50,301,308],"dysfunction.":[51],"To":[52,295],"best":[54,57],"our":[56],"knowledge,":[58],"all":[59,265],"approaches":[60],"automatic":[63],"detection":[64,167,218],"consider":[68],"hand-crafted":[69],"features.":[70],"This":[71],"paper":[72],"reports":[73],"first":[75,96,123,242],"deep-learning-based":[76],"approach":[77,352],"developed":[78,137,163],"real-time":[81,358],"The":[87,122,132,158,188,252,278,346],"proposed":[88,317,351],"DHN":[89,318],"consists":[90],"three":[92],"component":[93,124,134,160,186],"networks:":[94],"detects":[97,103,117,322],"subject\u2019s":[99],"face,":[100,113],"second":[102,133,185],"landmarks":[106,154,221],"line":[108,146,156,180,206,213],"segments":[109,181],"on":[110,128,138,164,267],"detected":[112,182],"third":[116,159],"local":[119,223,324],"built":[127],"YOLO2":[130],"detector.":[131],"a":[139,145,198],"fused":[140],"architecture":[142],"incorporates":[144],"segment":[147,214],"learning":[148,215],"locating":[151],"segments.":[157],"an":[165,354],"object":[166],"with":[169],"line-segment-embedded":[171],"input":[172],"combines":[174],"landmarked":[176],"region":[177],"by":[183,292],"network.":[187],"novelties":[189],"this":[191],"research":[192],"include:":[193],"1)":[194],"modification":[196],"state-of-the-art":[199],"edge":[200],"detector":[201],"extracting":[203],"segments;":[207],"2)":[208],"embedding":[210],"regions;":[225],"3)":[226],"description":[229,342],"syndrome":[234,336],"intensity;":[235],"4)":[237],"release":[239],"clinically":[243],"labeled":[244,291],"database,":[245],"YouTube":[247,289],"Palsy":[249],"(YFP)":[250],"database.":[251],"making":[253,270],"YFP":[256,279],"database":[257,280,309],"solves":[258],"issue":[260],"previous":[262],"methods":[263,275],"were":[264],"evaluated":[266],"proprietary":[268],"databases,":[269],"comparison":[272],"different":[274],"extremely":[276],"difficult.":[277],"includes":[281],"32":[282],"videos":[283],"21":[285],"patients":[286],"collected":[287],"from":[288],"clinic":[293],"specialists.":[294],"enhance":[296],"robustness":[298],"against":[299],"variations,":[302],"we":[303],"CK+":[306],"training.":[312],"show":[314,348],"not":[319],"only":[320],"just":[321],"regions":[326],"but":[327],"captures":[329],"intensity":[331],"over":[337],"time,":[338],"enabling":[339],"syndrome.":[345],"experiments":[347],"offers":[353],"accurate":[355],"efficient":[357],"solution":[359],"analysis.":[363]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":18},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2026-06-21T07:57:09.225873","created_date":"2025-10-10T00:00:00"}