{"id":"https://openalex.org/W2074989593","doi":"https://doi.org/10.1109/avss.2014.6918650","title":"Exploiting the deep learning paradigm for recognizing human actions","display_name":"Exploiting the deep learning paradigm for recognizing human actions","publication_year":2014,"publication_date":"2014-08-01","ids":{"openalex":"https://openalex.org/W2074989593","doi":"https://doi.org/10.1109/avss.2014.6918650","mag":"2074989593"},"language":"en","primary_location":{"id":"doi:10.1109/avss.2014.6918650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2014.6918650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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/A5082731857","display_name":"Pasquale Foggia","orcid":"https://orcid.org/0000-0002-7096-1902"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Pasquale Foggia","raw_affiliation_strings":["Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","institution_ids":["https://openalex.org/I131729948"]},{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083939361","display_name":"Alessia Saggese","orcid":"https://orcid.org/0000-0003-4687-7994"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessia Saggese","raw_affiliation_strings":["Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","institution_ids":["https://openalex.org/I131729948"]},{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067565879","display_name":"Nicola Strisciuglio","orcid":"https://orcid.org/0000-0002-7478-3509"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nicola Strisciuglio","raw_affiliation_strings":["Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","institution_ids":["https://openalex.org/I131729948"]},{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027593663","display_name":"Mario Vento","orcid":"https://orcid.org/0000-0002-2948-741X"},"institutions":[{"id":"https://openalex.org/I131729948","display_name":"University of Salerno","ror":"https://ror.org/0192m2k53","country_code":"IT","type":"education","lineage":["https://openalex.org/I131729948"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mario Vento","raw_affiliation_strings":["Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics, University of Salerno, Fisciano, SA, Italy","institution_ids":["https://openalex.org/I131729948"]},{"raw_affiliation_string":"Dept. of Computer Eng. and Electrical Eng. and and Applied Mathematics University of Salerno Via Giovanni Paolo II, 132, Fisciano (SA), Italy","institution_ids":["https://openalex.org/I131729948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I131729948"],"apc_list":null,"apc_paid":null,"fwci":3.9556,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.96522059,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"93","last_page":"98"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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":0.9998999834060669,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9957000017166138,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8144761323928833},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.7705283164978027},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7658933997154236},{"id":"https://openalex.org/keywords/restricted-boltzmann-machine","display_name":"Restricted Boltzmann machine","score":0.6986098289489746},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.6639162302017212},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6113250851631165},{"id":"https://openalex.org/keywords/boltzmann-machine","display_name":"Boltzmann machine","score":0.5923829078674316},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5629558563232422},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.562606692314148},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5618407726287842},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.5366095900535583},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5036746859550476},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.49153169989585876},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.45946407318115234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4138944447040558},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07273897528648376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8144761323928833},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.7705283164978027},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7658933997154236},{"id":"https://openalex.org/C199354608","wikidata":"https://www.wikidata.org/wiki/Q7316287","display_name":"Restricted Boltzmann machine","level":3,"score":0.6986098289489746},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.6639162302017212},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6113250851631165},{"id":"https://openalex.org/C192576344","wikidata":"https://www.wikidata.org/wiki/Q194706","display_name":"Boltzmann machine","level":3,"score":0.5923829078674316},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5629558563232422},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.562606692314148},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5618407726287842},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.5366095900535583},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5036746859550476},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.49153169989585876},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.45946407318115234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4138944447040558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07273897528648376},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss.2014.6918650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss.2014.6918650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W28988658","https://openalex.org/W44815768","https://openalex.org/W128216765","https://openalex.org/W177678287","https://openalex.org/W189596042","https://openalex.org/W285288441","https://openalex.org/W1973445088","https://openalex.org/W1983364832","https://openalex.org/W1985364430","https://openalex.org/W1999192586","https://openalex.org/W2007964100","https://openalex.org/W2020295237","https://openalex.org/W2032304035","https://openalex.org/W2050874186","https://openalex.org/W2064630666","https://openalex.org/W2072128103","https://openalex.org/W2084846335","https://openalex.org/W2086509056","https://openalex.org/W2093559122","https://openalex.org/W2106996050","https://openalex.org/W2120919612","https://openalex.org/W2138726949","https://openalex.org/W2158699018","https://openalex.org/W2163922914","https://openalex.org/W2533739470","https://openalex.org/W4231109964","https://openalex.org/W6601175079","https://openalex.org/W6607775107","https://openalex.org/W6680658560"],"related_works":["https://openalex.org/W2064630666","https://openalex.org/W3121598771","https://openalex.org/W2287713958","https://openalex.org/W2513801676","https://openalex.org/W2916681395","https://openalex.org/W3010338767","https://openalex.org/W1257380361","https://openalex.org/W3005559199","https://openalex.org/W2133034788","https://openalex.org/W2892911634"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3],"propose":[4],"a":[5,14,19,33,43,49,59,92,102,106],"novel":[6],"method":[7],"for":[8],"recognizing":[9],"human":[10],"actions":[11],"by":[12,39,58,82],"exploiting":[13,85],"multi-layer":[15],"representation":[16,36,78,103],"based":[17,22],"on":[18,116],"deep":[20],"learning":[21],"architecture.":[23],"A":[24],"first":[25],"level":[26,35,77],"feature":[27],"vector":[28],"is":[29,37,55,79],"extracted":[30],"and":[31,120],"then":[32],"high":[34,76],"obtained":[38],"taking":[40],"advantage":[41,65],"of":[42,127],"Deep":[44],"Belief":[45],"Network":[46],"trained":[47],"using":[48],"Restricted":[50],"Boltzmann":[51],"Machine.":[52],"The":[53,63,110],"classification":[54],"finally":[56],"performed":[57],"feed-forward":[60],"neural":[61],"network.":[62],"main":[64],"behind":[66],"the":[67,72,75,83,86,89,121,128],"proposed":[68,111],"approach":[69,112],"lies":[70],"in":[71,88],"fact":[73],"that":[74,100],"automatically":[80],"built":[81],"system":[84],"regularities":[87],"dataset;":[90],"given":[91],"suitably":[93],"large":[94],"dataset,":[95],"it":[96],"can":[97,104],"be":[98],"expected":[99],"such":[101],"outperform":[105],"hand-design":[107],"description":[108],"scheme.":[109],"has":[113],"been":[114],"tested":[115],"two":[117],"standard":[118],"datasets":[119],"achieved":[122],"results,":[123],"compared":[124],"with":[125],"state":[126],"art":[129],"algorithms,":[130],"confirm":[131],"its":[132],"effectiveness.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
