{"id":"https://openalex.org/W2535110112","doi":"https://doi.org/10.1109/aipr.2015.7444550","title":"Improved Gait recognition based on specialized deep convolutional neural networks","display_name":"Improved Gait recognition based on specialized deep convolutional neural networks","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2535110112","doi":"https://doi.org/10.1109/aipr.2015.7444550","mag":"2535110112"},"language":"en","primary_location":{"id":"doi:10.1109/aipr.2015.7444550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2015.7444550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5031684481","display_name":"Munif Alotaibi","orcid":null},"institutions":[{"id":"https://openalex.org/I154300980","display_name":"University of Bridgeport","ror":"https://ror.org/01rf3yp57","country_code":"US","type":"education","lineage":["https://openalex.org/I154300980"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Munif Alotaibi","raw_affiliation_strings":["Computer Science and Engineering Department, University of Bridgeport"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, University of Bridgeport","institution_ids":["https://openalex.org/I154300980"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005346248","display_name":"Ausif Mahmood","orcid":"https://orcid.org/0000-0002-8991-4268"},"institutions":[{"id":"https://openalex.org/I154300980","display_name":"University of Bridgeport","ror":"https://ror.org/01rf3yp57","country_code":"US","type":"education","lineage":["https://openalex.org/I154300980"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ausif Mahmood","raw_affiliation_strings":["Computer Science and Engineering Department, University of Bridgeport"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science and Engineering Department, University of Bridgeport","institution_ids":["https://openalex.org/I154300980"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154300980"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":51,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":1.0,"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":1.0,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9710000157356262,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9657999873161316,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.8317006826400757},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7963728904724121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7925623655319214},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.7402138113975525},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.6682310700416565},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.655839204788208},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5755141377449036},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5135765075683594},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41693758964538574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3646315336227417}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8317006826400757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963728904724121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7925623655319214},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.7402138113975525},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.6682310700416565},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.655839204788208},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5755141377449036},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5135765075683594},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41693758964538574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3646315336227417},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C42407357","wikidata":"https://www.wikidata.org/wiki/Q521","display_name":"Physiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr.2015.7444550","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2015.7444550","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W17401670","https://openalex.org/W1964792465","https://openalex.org/W1974775426","https://openalex.org/W1975036395","https://openalex.org/W1986895792","https://openalex.org/W2016053056","https://openalex.org/W2018331988","https://openalex.org/W2018480038","https://openalex.org/W2038176251","https://openalex.org/W2039141295","https://openalex.org/W2078046692","https://openalex.org/W2084796520","https://openalex.org/W2097117768","https://openalex.org/W2097290407","https://openalex.org/W2104335344","https://openalex.org/W2118036996","https://openalex.org/W2121647436","https://openalex.org/W2126680226","https://openalex.org/W2127964696","https://openalex.org/W2130278361","https://openalex.org/W2135541996","https://openalex.org/W2138451337","https://openalex.org/W2143583134","https://openalex.org/W2145421913","https://openalex.org/W2149516292","https://openalex.org/W2154624311","https://openalex.org/W2163605009","https://openalex.org/W2542803194","https://openalex.org/W6674914833","https://openalex.org/W6675575696","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W3185413894","https://openalex.org/W1905194803","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W2137411393","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2386960251"],"abstract_inverted_index":{"Gait":[0,28],"recognition":[1,29,59,141,196],"is":[2,7,31,76,124],"a":[3,40,50,70,99,107],"biometric":[4],"technique":[5,123],"that":[6,85,136,157,180],"used":[8,160],"in":[9,98,161,186,198],"order":[10],"to":[11,57,89,127,171],"determine":[12],"the":[13,19,22,63,79,87,131,145,148,166,176,181,190],"identity":[14],"of":[15,24,65,78,114,116,130,147,193],"humans":[16],"based":[17],"on":[18,62],"style":[20],"and":[21,45,49,118,134,138],"manner":[23],"their":[25],"walk.":[26],"Yet,":[27],"performance":[30],"often":[32],"degraded":[33],"by":[34],"some":[35],"covariate":[36],"factors":[37],"such":[38],"as":[39],"viewing":[41],"angle":[42],"variation,":[43],"clothing":[44],"carrying":[46],"condition":[47],"changes,":[48],"low-image":[51],"resolution.":[52],"In":[53,102],"general,":[54],"current":[55],"tactics":[56],"object":[58],"highly":[60],"depend":[61],"use":[64,146],"machine":[66,82],"learning":[67,83,151],"techniques.":[68],"Therefore,":[69],"deep":[71,109,168,182],"convolutional":[72,117],"neural":[73],"network":[74],"(CNN)":[75],"one":[77],"most":[80],"advanced":[81],"techniques":[84,197],"has":[86],"ability":[88],"approximate":[90],"complex":[91],"non-linear":[92],"functions":[93],"from":[94],"high-dimensional":[95],"input":[96],"data":[97],"hierarchical":[100],"process.":[101],"this":[103,187],"paper,":[104],"we":[105],"develop":[106],"specialized":[108],"CNN":[110,169,183],"architecture,":[111],"which":[112],"consists":[113],"multilayers":[115],"subsampling":[119],"layers.":[120],"The":[121],"proposed":[122,167],"less":[125],"sensitive":[126],"several":[128,199],"cases":[129],"common":[132],"variations":[133],"occlusions":[135],"affect":[137],"degrade":[139],"gait":[140,162,174,195],"performance.":[142],"We":[143],"avoided":[144],"typical":[149],"subspace":[150],"methods,":[152],"along":[153],"with":[154],"its":[155],"shortcomings,":[156],"are":[158],"widely":[159],"recognition.":[163],"When":[164],"applied":[165],"model":[170,184],"CASIA-B":[172],"large":[173],"database,":[175],"experimental":[177],"results":[178],"show":[179],"developed":[185],"paper":[188],"outperforms":[189],"other":[191],"state":[192],"art":[194],"cases.":[200]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}