{"id":"https://openalex.org/W2728572167","doi":"https://doi.org/10.1109/siu.2017.7960446","title":"Video action classification by deep learning","display_name":"Video action classification by deep learning","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2728572167","doi":"https://doi.org/10.1109/siu.2017.7960446","mag":"2728572167"},"language":"en","primary_location":{"id":"doi:10.1109/siu.2017.7960446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2017.7960446","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-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/A5013571818","display_name":"Esra Erg\u00fcn","orcid":"https://orcid.org/0000-0001-5000-8543"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Esra Ergun","raw_affiliation_strings":["\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066311018","display_name":"Filiz G\u00fcrkan","orcid":"https://orcid.org/0000-0002-9857-3012"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Filiz Gurkan","raw_affiliation_strings":["\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044041024","display_name":"Onur Kaplan","orcid":"https://orcid.org/0000-0002-0759-621X"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Onur Kaplan","raw_affiliation_strings":["\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I48912391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089754740","display_name":"Bilge G\u00fcnsel","orcid":"https://orcid.org/0000-0003-3628-3316"},"institutions":[{"id":"https://openalex.org/I48912391","display_name":"Istanbul Technical University","ror":"https://ror.org/059636586","country_code":"TR","type":"education","lineage":["https://openalex.org/I48912391"]}],"countries":["TR"],"is_corresponding":false,"raw_author_name":"Bilge Gunsel","raw_affiliation_strings":["\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye"],"affiliations":[{"raw_affiliation_string":"\u00c7o\u011fulortam \u0131\u015faret \u0130\u015fleme ve \u00d6r\u00fcnt\u00fc Tan\u0131ma Grubu, \u0130stanbul Teknik \u00dcniversitesi, \u0130stanbul, T\u00fcrkiye","institution_ids":["https://openalex.org/I48912391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5013571818"],"corresponding_institution_ids":["https://openalex.org/I48912391"],"apc_list":null,"apc_paid":null,"fwci":0.0923,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.45205819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9987000226974487,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.8123904466629028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7440047860145569},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6808315515518188},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5857547521591187},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.5183275938034058},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5149508118629456},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5135059952735901},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4970536530017853},{"id":"https://openalex.org/keywords/video-content-analysis","display_name":"Video content analysis","score":0.46425870060920715},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.4627762734889984},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41569364070892334},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3949507176876068},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.3043668866157532},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.2974994480609894},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09503349661827087}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8123904466629028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7440047860145569},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6808315515518188},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5857547521591187},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.5183275938034058},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5149508118629456},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5135059952735901},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4970536530017853},{"id":"https://openalex.org/C2778598663","wikidata":"https://www.wikidata.org/wiki/Q1407599","display_name":"Video content analysis","level":4,"score":0.46425870060920715},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.4627762734889984},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41569364070892334},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3949507176876068},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.3043668866157532},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.2974994480609894},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09503349661827087}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/siu.2017.7960446","is_oa":false,"landing_page_url":"https://doi.org/10.1109/siu.2017.7960446","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 25th Signal Processing and Communications Applications Conference (SIU)","raw_type":"proceedings-article"},{"id":"pmh:oai:polen.itu.edu.tr:11527/34786","is_oa":false,"landing_page_url":"https://hdl.handle.net/11527/34786","pdf_url":null,"source":{"id":"https://openalex.org/S4306400460","display_name":"Istanbul Technical University Academic Open Archive (Istanbul Technical University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I48912391","host_organization_name":"Istanbul Technical University","host_organization_lineage":["https://openalex.org/I48912391"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6299999952316284,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1867429401","https://openalex.org/W1947481528","https://openalex.org/W2016053056","https://openalex.org/W2064675550","https://openalex.org/W2090518410","https://openalex.org/W2136848157","https://openalex.org/W2152231592","https://openalex.org/W2163605009","https://openalex.org/W2281613842","https://openalex.org/W6682507636","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2971088694","https://openalex.org/W2562733635","https://openalex.org/W2077468687","https://openalex.org/W2347818423","https://openalex.org/W158481387","https://openalex.org/W3096648924","https://openalex.org/W2746669491","https://openalex.org/W2075992917","https://openalex.org/W2161605020","https://openalex.org/W2065692323"],"abstract_inverted_index":{"The":[0,18],"purpose":[1],"of":[2,9,55,66],"this":[3,39,102],"study":[4,40],"is":[5,22,44,79,111],"learning":[6,78,88,97],"and":[7,15,33,62,98,117,119,170],"classification":[8,99,174],"video":[10,13,19,29,41,108,172],"activities":[11],"using":[12,113],"color":[14,90,120],"motion":[16,92,109,118,162,173],"information.":[17],"activity":[20,42,125,141],"labeling":[21],"important":[23],"for":[24,124],"many":[25],"applications":[26],"such":[27,148],"as":[28,149],"content":[30,110],"modeling,":[31],"indexing,":[32],"quick":[34],"access":[35],"to":[36,51,95,160],"content.":[37],"In":[38,49,101],"recognition":[43],"performed":[45,80,129],"by":[46,81],"deep":[47,87],"learning.":[48],"order":[50],"learn":[52],"visual":[53],"features":[54,121],"video,":[56],"Convolutional":[57],"Neural":[58],"Network":[59],"(CNN)":[60],"layers":[61,73],"a":[63,131],"special":[64],"type":[65],"recursive":[67],"networks,":[68],"Long-Short":[69],"Term":[70],"Memory":[71],"(LSTM),":[72],"are":[74,122],"stacked.":[75],"Video":[76],"sequence":[77],"end-to-end":[82],"training.":[83],"Recent":[84],"works":[85],"on":[86,130],"employ":[89],"end":[91],"information":[93,163],"together":[94],"improve":[96],"accuracy.":[100],"study,":[103],"unlike":[104],"the":[105],"existing":[106],"models,":[107],"learned":[112],"SIFT":[114,155],"flow":[115,156,168],"vectors":[116,157,169],"fused":[123],"recognition.":[126],"Performance":[127],"tests":[128],"commonly":[132],"used":[133],"benchmarking":[134],"data":[135],"set,":[136],"UCF":[137],"101":[138,145],"which":[139],"includes":[140],"labeled":[142],"videos":[143],"from":[144],"action":[146],"categories":[147],"\"Biking\",":[150],"\"Playing":[151],"Guitar,\"":[152],"demonstrate":[153],"that":[154],"allow":[158],"us":[159],"model":[161],"more":[164],"accurately":[165],"than":[166],"optical":[167],"increase":[171],"performance.":[175]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-06T13:50:29.536080","created_date":"2025-10-10T00:00:00"}