{"id":"https://openalex.org/W3049475126","doi":"https://doi.org/10.1109/tsp49548.2020.9163464","title":"A Robust Deep Model for Human Action Recognition in Restricted Video Sequences","display_name":"A Robust Deep Model for Human Action Recognition in Restricted Video Sequences","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3049475126","doi":"https://doi.org/10.1109/tsp49548.2020.9163464","mag":"3049475126"},"language":"en","primary_location":{"id":"doi:10.1109/tsp49548.2020.9163464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp49548.2020.9163464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 43rd International Conference on Telecommunications and Signal Processing (TSP)","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/A5090289947","display_name":"Vahid Ashkani Chenarlogh","orcid":"https://orcid.org/0000-0003-2074-9863"},"institutions":[{"id":"https://openalex.org/I155419210","display_name":"Islamic Azad University, Science and Research Branch","ror":"https://ror.org/03187yj51","country_code":"IR","type":"education","lineage":["https://openalex.org/I110525433","https://openalex.org/I155419210"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Vahid Ashkani Chenarlogh","raw_affiliation_strings":["ECE Department, Islamic Azad University Science and Research Branch, Tehran, Iran"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE Department, Islamic Azad University Science and Research Branch, Tehran, Iran","institution_ids":["https://openalex.org/I155419210"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032953618","display_name":"Hossein B. Jond","orcid":"https://orcid.org/0000-0002-8418-805X"},"institutions":[{"id":"https://openalex.org/I142208455","display_name":"VSB - Technical University of Ostrava","ror":"https://ror.org/05x8mcb75","country_code":"CZ","type":"education","lineage":["https://openalex.org/I142208455"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Hossein B Jond","raw_affiliation_strings":["Department of Computer Science, VSB \u2013 Technical University of Ostrava, Ostrava, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, VSB \u2013 Technical University of Ostrava, Ostrava, Czech Republic","institution_ids":["https://openalex.org/I142208455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038161265","display_name":"Jan Plato\u0161","orcid":"https://orcid.org/0000-0002-8481-0136"},"institutions":[{"id":"https://openalex.org/I142208455","display_name":"VSB - Technical University of Ostrava","ror":"https://ror.org/05x8mcb75","country_code":"CZ","type":"education","lineage":["https://openalex.org/I142208455"]}],"countries":["CZ"],"is_corresponding":false,"raw_author_name":"Jan Platos","raw_affiliation_strings":["Department of Computer Science, VSB \u2013 Technical University of Ostrava, Ostrava, Czech Republic"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, VSB \u2013 Technical University of Ostrava, Ostrava, Czech Republic","institution_ids":["https://openalex.org/I142208455"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1958,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49826245,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"7065","issue":null,"first_page":"541","last_page":"544"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9980000257492065,"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":0.995199978351593,"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/robustness","display_name":"Robustness (evolution)","score":0.8388083577156067},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8054585456848145},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.7031333446502686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7028281092643738},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6966100931167603},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6480257511138916},{"id":"https://openalex.org/keywords/long-short-term-memory","display_name":"Long short term memory","score":0.5862293243408203},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5243632793426514},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3870460093021393},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.32747042179107666},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3244306147098541}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.8388083577156067},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8054585456848145},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.7031333446502686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7028281092643738},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6966100931167603},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6480257511138916},{"id":"https://openalex.org/C133488467","wikidata":"https://www.wikidata.org/wiki/Q6673524","display_name":"Long short term memory","level":4,"score":0.5862293243408203},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5243632793426514},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3870460093021393},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.32747042179107666},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3244306147098541},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tsp49548.2020.9163464","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsp49548.2020.9163464","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 43rd International Conference on Telecommunications and Signal Processing (TSP)","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":24,"referenced_works":["https://openalex.org/W28988658","https://openalex.org/W846669277","https://openalex.org/W1686810756","https://openalex.org/W2000059041","https://openalex.org/W2058580716","https://openalex.org/W2064675550","https://openalex.org/W2100916003","https://openalex.org/W2176950688","https://openalex.org/W2583946517","https://openalex.org/W2594395650","https://openalex.org/W2600446833","https://openalex.org/W2685712812","https://openalex.org/W2755624598","https://openalex.org/W2765651845","https://openalex.org/W2769581371","https://openalex.org/W2886690463","https://openalex.org/W2891290365","https://openalex.org/W2902376510","https://openalex.org/W2910455154","https://openalex.org/W2945096417","https://openalex.org/W2980037812","https://openalex.org/W6601175079","https://openalex.org/W6637373629","https://openalex.org/W6745268276"],"related_works":["https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W3008584592","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3167935049","https://openalex.org/W3029198973","https://openalex.org/W2912153778","https://openalex.org/W4387163678"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"an":[5],"action":[6],"recognition":[7],"algorithm":[8,78,101],"in":[9,65,106],"noisy":[10,107],"data":[11,109],"conditions":[12],"with":[13],"Convolutional":[14],"Neural":[15],"Network":[16],"(CNN)":[17],"as":[18,30,110],"the":[19,31,39,54,73,89,99,111],"front":[20],"end":[21],"and":[22,68,83,94],"Deep":[23],"Bidirectional":[24],"Long":[25],"Short":[26],"Term":[27],"Memory":[28],"(DBi-LSTM)":[29],"backend.":[32],"The":[33,46,76],"deep":[34],"features":[35],"are":[36],"extracted":[37],"from":[38],"input":[40],"frames":[41,50],"using":[42,53],"a":[43],"VGG16":[44],"model.":[45],"sequential":[47],"information":[48],"among":[49],"is":[51,58],"learned":[52],"DBi-LSTM":[55],"part,":[56],"which":[57],"composed":[59],"of":[60,88],"three":[61],"layers":[62],"stacked":[63],"together":[64],"both":[66],"forward":[67],"backward":[69],"directions":[70],"to":[71],"increase":[72],"learning":[74],"depth.":[75],"proposed":[77,100],"achieved":[79],"96.77%":[80],"vs.":[81,85],"96.76%":[82],"95.83%":[84],"91.60%":[86],"accuracy":[87,112],"baseline":[90],"methods":[91],"on":[92],"KTH":[93],"YouTube":[95],"datasets,":[96],"respectively.":[97],"Moreover,":[98],"has":[102],"shown":[103],"significant":[104],"robustness":[105],"training":[108],"drops":[113],"only":[114],"1%":[115],"down.":[116]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}