{"id":"https://openalex.org/W2897874865","doi":"https://doi.org/10.1109/access.2018.2876890","title":"Gait-Based Human Identification by Combining Shallow Convolutional Neural Network-Stacked Long Short-Term Memory and Deep Convolutional Neural Network","display_name":"Gait-Based Human Identification by Combining Shallow Convolutional Neural Network-Stacked Long Short-Term Memory and Deep Convolutional Neural Network","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2897874865","doi":"https://doi.org/10.1109/access.2018.2876890","mag":"2897874865"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2876890","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2876890","pdf_url":null,"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://doi.org/10.1109/access.2018.2876890","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086481810","display_name":"Ganbayar Batchuluun","orcid":"https://orcid.org/0000-0003-1456-5697"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Ganbayar Batchuluun","raw_affiliation_strings":["Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060349162","display_name":"Hyo Sik Yoon","orcid":null},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyo Sik Yoon","raw_affiliation_strings":["Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018168347","display_name":"Jin Kyu Kang","orcid":"https://orcid.org/0000-0001-9293-4502"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jin Kyu Kang","raw_affiliation_strings":["Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083173630","display_name":"Kang Ryoung Park","orcid":"https://orcid.org/0000-0002-1214-9510"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kang Ryoung Park","raw_affiliation_strings":["Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-1214-9510","affiliations":[{"raw_affiliation_string":"Division of Electronics and Electrical Engineering, Dongguk University, Seoul, South Korea","institution_ids":["https://openalex.org/I205490536"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5086481810"],"corresponding_institution_ids":["https://openalex.org/I205490536"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.1173,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.87031303,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"63164","last_page":"63186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9983000159263611,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9941999912261963,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8767653703689575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8378702402114868},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8024251461029053},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.7399823069572449},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.5699269771575928},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5353356599807739},{"id":"https://openalex.org/keywords/cadence","display_name":"Cadence","score":0.5140656232833862},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5000979900360107},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4964514374732971},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.41591671109199524},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.065593421459198}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8767653703689575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8378702402114868},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8024251461029053},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7399823069572449},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.5699269771575928},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5353356599807739},{"id":"https://openalex.org/C2777125575","wikidata":"https://www.wikidata.org/wiki/Q14088448","display_name":"Cadence","level":2,"score":0.5140656232833862},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5000979900360107},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4964514374732971},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.41591671109199524},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.065593421459198},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C42407357","wikidata":"https://www.wikidata.org/wiki/Q521","display_name":"Physiology","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2876890","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2876890","pdf_url":null,"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:9960f2f2c2ef40408c46e97f4601b962","is_oa":true,"landing_page_url":"https://doaj.org/article/9960f2f2c2ef40408c46e97f4601b962","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 6, Pp 63164-63186 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2876890","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2876890","pdf_url":null,"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/G1738276608","display_name":null,"funder_award_id":"NRF-2017R1C1B5074062","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G3515857073","display_name":null,"funder_award_id":"NRF-2018R1D1A1B07041921","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G6837306824","display_name":null,"funder_award_id":"NRF-2017R1D1A1B03028417","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W175911620","https://openalex.org/W1496923160","https://openalex.org/W1522301498","https://openalex.org/W1546677826","https://openalex.org/W1552433757","https://openalex.org/W1686810756","https://openalex.org/W1689711448","https://openalex.org/W1811254738","https://openalex.org/W1895577753","https://openalex.org/W1953543587","https://openalex.org/W1971955426","https://openalex.org/W2022075901","https://openalex.org/W2049135373","https://openalex.org/W2064675550","https://openalex.org/W2085601296","https://openalex.org/W2112796928","https://openalex.org/W2113408265","https://openalex.org/W2138451337","https://openalex.org/W2145287260","https://openalex.org/W2163605009","https://openalex.org/W2183341477","https://openalex.org/W2194775991","https://openalex.org/W2275614026","https://openalex.org/W2295124130","https://openalex.org/W2307035320","https://openalex.org/W2309606390","https://openalex.org/W2322772590","https://openalex.org/W2325939864","https://openalex.org/W2392949088","https://openalex.org/W2473640056","https://openalex.org/W2508429489","https://openalex.org/W2510190030","https://openalex.org/W2517225990","https://openalex.org/W2531409750","https://openalex.org/W2545177271","https://openalex.org/W2590203987","https://openalex.org/W2592878160","https://openalex.org/W2609963459","https://openalex.org/W2612587170","https://openalex.org/W2612627974","https://openalex.org/W2745436507","https://openalex.org/W2770546254","https://openalex.org/W2781880940","https://openalex.org/W2793239857","https://openalex.org/W2889203925","https://openalex.org/W2951327905","https://openalex.org/W2952587893","https://openalex.org/W2962706528","https://openalex.org/W2963216120","https://openalex.org/W2963446712","https://openalex.org/W2963589138","https://openalex.org/W2963998561","https://openalex.org/W2964081807","https://openalex.org/W2964121744","https://openalex.org/W2964350391","https://openalex.org/W3105827609","https://openalex.org/W4206519171","https://openalex.org/W6632557493","https://openalex.org/W6638742206","https://openalex.org/W6641024474","https://openalex.org/W6677051090","https://openalex.org/W6684191040","https://openalex.org/W6694260854","https://openalex.org/W6698200468","https://openalex.org/W6698262075","https://openalex.org/W6737391450"],"related_works":["https://openalex.org/W2953508068","https://openalex.org/W2097954104","https://openalex.org/W2087026446","https://openalex.org/W4210601529","https://openalex.org/W2150212084","https://openalex.org/W4247927490","https://openalex.org/W2422104739","https://openalex.org/W98595376","https://openalex.org/W2144747704","https://openalex.org/W2601292506"],"abstract_inverted_index":{"Human":[0],"identification":[1,124],"using":[2,54,184],"camera-based":[3],"surveillance":[4],"systems":[5],"is":[6,18],"a":[7,118,185],"challenging":[8],"research":[9],"topic,":[10],"especially":[11],"in":[12,136,175],"cases":[13],"where":[14],"the":[15,40,51,77,127,154,168,189,193,206],"human":[16,52,69,123],"face":[17],"not":[19],"visible":[20],"to":[21,35,106,143],"cameras":[22,28],"and/or":[23],"when":[24],"humans":[25,134],"captured":[26,135,174],"on":[27,50,126],"have":[29,64,76,116],"no":[30],"clear":[31],"visual":[32],"identity":[33],"owing":[34],"environments":[36],"with":[37,97],"low-illumination.":[38],"With":[39],"development":[41],"of":[42,79,83,133,156,192,195,199],"deep":[43,100],"learning":[44],"algorithms,":[45],"studies":[46,120],"that":[47,205],"are":[48],"based":[49,125],"gait":[53,201],"convolutional":[55],"neural":[56],"networks":[57],"(CNNs)":[58],"and":[59,73,85,99,110,129,153,170,188],"long":[60],"short-term":[61],"memory":[62],"(LSTM)":[63],"achieved":[65],"promising":[66],"performance":[67],"for":[68],"identification.":[70],"However,":[71],"CNN":[72,95,101],"LSTM-based":[74],"methods":[75],"limitation":[78],"having":[80],"higher":[81],"loss":[82],"temporal":[84,111],"spatial":[86,109],"information,":[87],"respectively.":[88],"In":[89,113],"our":[90,165],"approach,":[91],"we":[92,163],"use":[93],"shallow":[94],"stacked":[96],"LSTM":[98],"followed":[102],"by":[103],"score":[104],"fusion":[105],"capture":[107],"more":[108],"features.":[112],"addition,":[114],"there":[115],"been":[117],"few":[119],"regarding":[121],"gait-based":[122],"front":[128,169],"back":[130,171],"view":[131,172],"images":[132,173],"low-illumination":[137],"environments.":[138,179],"This":[139],"makes":[140],"it":[141],"difficult":[142],"extract":[144],"conventional":[145],"features,":[146],"such":[147],"as":[148],"skeleton":[149],"joints,":[150],"cycle,":[151],"cadence,":[152],"lengths":[155],"walking":[157],"strides.":[158],"To":[159],"overcome":[160],"these":[161],"problems,":[162],"designed":[164],"method":[166,208],"considering":[167],"both":[176],"highand":[177],"lowillumination":[178],"The":[180],"experimental":[181],"results":[182],"obtained":[183],"self-collected":[186],"database":[187,191],"open":[190],"institute":[194],"automation":[196],"Chinese":[197],"academy":[198],"sciences":[200],"dataset":[202],"C":[203],"show":[204],"proposed":[207],"outperforms":[209],"previous":[210],"methods.":[211]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":11},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":5},{"year":2014,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
