{"id":"https://openalex.org/W3154930930","doi":"https://doi.org/10.3390/sym13040662","title":"Hi-EADN: Hierarchical Excitation Aggregation and Disentanglement Frameworks for Action Recognition Based on Videos","display_name":"Hi-EADN: Hierarchical Excitation Aggregation and Disentanglement Frameworks for Action Recognition Based on Videos","publication_year":2021,"publication_date":"2021-04-12","ids":{"openalex":"https://openalex.org/W3154930930","doi":"https://doi.org/10.3390/sym13040662","mag":"3154930930"},"language":"en","primary_location":{"id":"doi:10.3390/sym13040662","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13040662","pdf_url":"https://www.mdpi.com/2073-8994/13/4/662/pdf?version=1618237039","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-8994/13/4/662/pdf?version=1618237039","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058151558","display_name":"Zeyuan Hu","orcid":"https://orcid.org/0000-0002-3673-356X"},"institutions":[{"id":"https://openalex.org/I4210104306","display_name":"Tongmyong University","ror":"https://ror.org/01asa8g02","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210104306"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Zeyuan Hu","raw_affiliation_strings":["Department of Information Communication Engineering, Tongmyong University, Busan 48520, Korea"],"raw_orcid":"https://orcid.org/0000-0002-3673-356X","affiliations":[{"raw_affiliation_string":"Department of Information Communication Engineering, Tongmyong University, Busan 48520, Korea","institution_ids":["https://openalex.org/I4210104306"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108241503","display_name":"Eung-Joo Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I4210104306","display_name":"Tongmyong University","ror":"https://ror.org/01asa8g02","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210104306"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Eung-Joo Lee","raw_affiliation_strings":["Department of Information Communication Engineering, Tongmyong University, Busan 48520, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Communication Engineering, Tongmyong University, Busan 48520, Korea","institution_ids":["https://openalex.org/I4210104306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5058151558"],"corresponding_institution_ids":["https://openalex.org/I4210104306"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2227},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2227},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03628369,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"4","first_page":"662","last_page":"662"},"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":0.9944000244140625,"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/T11227","display_name":"Diabetic Foot Ulcer Assessment and Management","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7930020093917847},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7757918238639832},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7034414410591125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5880581736564636},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5658278465270996},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5597838759422302},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.53792804479599},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5128360390663147},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5093017816543579},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.48418930172920227},{"id":"https://openalex.org/keywords/excitation","display_name":"Excitation","score":0.4590550661087036},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06582453846931458},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.05581927299499512}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7930020093917847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7757918238639832},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7034414410591125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5880581736564636},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5658278465270996},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5597838759422302},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.53792804479599},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5128360390663147},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5093017816543579},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.48418930172920227},{"id":"https://openalex.org/C83581075","wikidata":"https://www.wikidata.org/wiki/Q1361503","display_name":"Excitation","level":2,"score":0.4590550661087036},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06582453846931458},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.05581927299499512},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/sym13040662","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13040662","pdf_url":"https://www.mdpi.com/2073-8994/13/4/662/pdf?version=1618237039","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7a17ed0a91be48fd82c0edb9cab9449b","is_oa":true,"landing_page_url":"https://doaj.org/article/7a17ed0a91be48fd82c0edb9cab9449b","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":"Symmetry, Vol 13, Iss 4, p 662 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2073-8994/13/4/662/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/sym13040662","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Symmetry; Volume 13; Issue 4; Pages: 662","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/sym13040662","is_oa":true,"landing_page_url":"https://doi.org/10.3390/sym13040662","pdf_url":"https://www.mdpi.com/2073-8994/13/4/662/pdf?version=1618237039","source":{"id":"https://openalex.org/S190787756","display_name":"Symmetry","issn_l":"2073-8994","issn":["2073-8994"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Symmetry","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.6100000143051147,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3154930930.pdf"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W237546731","https://openalex.org/W1923404803","https://openalex.org/W1983364832","https://openalex.org/W2010638141","https://openalex.org/W2016053056","https://openalex.org/W2308045930","https://openalex.org/W2507009361","https://openalex.org/W2508429489","https://openalex.org/W2553594924","https://openalex.org/W2573794412","https://openalex.org/W2751841288","https://openalex.org/W2764289073","https://openalex.org/W2779911909","https://openalex.org/W2806990378","https://openalex.org/W2883411722","https://openalex.org/W2883723049","https://openalex.org/W2886479397","https://openalex.org/W2892711625","https://openalex.org/W2894841935","https://openalex.org/W2950971447","https://openalex.org/W2952005526","https://openalex.org/W2952186347","https://openalex.org/W2953070204","https://openalex.org/W2953352063","https://openalex.org/W2954146807","https://openalex.org/W2963446712","https://openalex.org/W2964308810","https://openalex.org/W2973083596","https://openalex.org/W2979631981","https://openalex.org/W2987855387","https://openalex.org/W2990541775","https://openalex.org/W2999794487","https://openalex.org/W3000273670","https://openalex.org/W3000936791","https://openalex.org/W3004308475","https://openalex.org/W3011074480","https://openalex.org/W3015417922","https://openalex.org/W3035413240","https://openalex.org/W3037347183","https://openalex.org/W3047092785","https://openalex.org/W3097032500","https://openalex.org/W3098745339","https://openalex.org/W3103858256","https://openalex.org/W3115524909","https://openalex.org/W3128636476","https://openalex.org/W6653080432","https://openalex.org/W6755099854"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W4230315250"],"abstract_inverted_index":{"Most":[0],"existing":[1],"video":[2],"action":[3],"recognition":[4],"methods":[5],"mainly":[6],"rely":[7],"on":[8,137],"high-level":[9],"semantic":[10],"information":[11,23,104],"from":[12],"convolutional":[13],"neural":[14],"networks":[15,49],"(CNNs)":[16],"but":[17],"ignore":[18],"the":[19,75,87,122,138,145],"discrepancies":[20],"of":[21,89,110,124],"different":[22,125],"streams.":[24],"However,":[25],"it":[26],"does":[27],"not":[28],"normally":[29],"consider":[30],"both":[31],"long-distance":[32],"aggregations":[33,117],"and":[34,47,58,73,93,112,114,140,150],"short-range":[35],"motions.":[36],"Thus,":[37],"to":[38,85],"solve":[39],"these":[40,83],"problems,":[41],"we":[42],"propose":[43],"hierarchical":[44,62],"excitation":[45,55],"aggregation":[46,56],"disentanglement":[48,63],"(Hi-EADNs),":[50],"which":[51],"include":[52],"multiple":[53,115],"frame":[54],"(MFEA)":[57],"a":[59,108],"feature":[60,92,103],"squeeze-and-excitation":[61],"(SEHD)":[64],"module.":[65],"MFEA":[66],"specifically":[67],"uses":[68],"long-short":[69],"range":[70],"motion":[71,126],"modelling":[72],"calculates":[74],"feature-level":[76],"temporal":[77,116],"difference.":[78],"The":[79],"SEHD":[80],"module":[81],"utilizes":[82],"differences":[84],"optimize":[86],"weights":[88],"each":[90],"spatiotemporal":[91],"excite":[94],"motion-sensitive":[95],"channels.":[96],"Moreover,":[97],"without":[98],"introducing":[99],"additional":[100],"parameters,":[101],"this":[102],"is":[105,148],"processed":[106],"with":[107,118],"series":[109],"squeezes":[111],"excitations,":[113],"neighbourhoods":[119],"can":[120],"enhance":[121],"interaction":[123],"frames.":[127],"Extensive":[128],"experimental":[129],"results":[130],"confirm":[131],"our":[132],"proposed":[133],"Hi-EADN":[134],"method":[135],"effectiveness":[136],"UCF101":[139],"HMDB51":[141],"benchmark":[142],"datasets,":[143],"where":[144],"top-5":[146],"accuracy":[147],"93.5%":[149],"76.96%.":[151]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
