{"id":"https://openalex.org/W4391093493","doi":"https://doi.org/10.1109/iciscae59047.2023.10392881","title":"Research on Action Pattern Recognition Based on DeepConvLSTM","display_name":"Research on Action Pattern Recognition Based on DeepConvLSTM","publication_year":2023,"publication_date":"2023-09-23","ids":{"openalex":"https://openalex.org/W4391093493","doi":"https://doi.org/10.1109/iciscae59047.2023.10392881"},"language":"en","primary_location":{"id":"doi:10.1109/iciscae59047.2023.10392881","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iciscae59047.2023.10392881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE)","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":null,"display_name":"Pengkai Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengkai Guo","raw_affiliation_strings":["Hohai University,School of Artificial Intelligence and Automation,Nanjing,China","School of Artificial Intelligence and Automation, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Hohai University,School of Artificial Intelligence and Automation,Nanjing,China","institution_ids":["https://openalex.org/I163340411"]},{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100448035","display_name":"Zhuo Li","orcid":"https://orcid.org/0000-0002-9296-2738"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhuo Li","raw_affiliation_strings":["Hohai University,School of Artificial Intelligence and Automation,Nanjing,China","School of Artificial Intelligence and Automation, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Hohai University,School of Artificial Intelligence and Automation,Nanjing,China","institution_ids":["https://openalex.org/I163340411"]},{"raw_affiliation_string":"School of Artificial Intelligence and Automation, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108630063","display_name":"Yiyan Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyan Sun","raw_affiliation_strings":["Hohai University,College of Energy and Electrical Engineering,Nanjing,China","College of Energy and Electrical Engineering, Hohai University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Hohai University,College of Energy and Electrical Engineering,Nanjing,China","institution_ids":["https://openalex.org/I163340411"]},{"raw_affiliation_string":"College of Energy and Electrical Engineering, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I163340411"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19586264,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":null,"first_page":"1100","last_page":"1105"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.991599977016449,"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/overfitting","display_name":"Overfitting","score":0.8749172687530518},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7321639657020569},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5911173820495605},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5512300133705139},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5231736302375793},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.49784302711486816},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.496126264333725},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.49146878719329834},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.443353533744812},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38885146379470825},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15987420082092285}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8749172687530518},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7321639657020569},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5911173820495605},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5512300133705139},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5231736302375793},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.49784302711486816},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.496126264333725},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.49146878719329834},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.443353533744812},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38885146379470825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15987420082092285},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","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/iciscae59047.2023.10392881","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iciscae59047.2023.10392881","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 6th International Conference on Information Systems and Computer Aided Education (ICISCAE)","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":6,"referenced_works":["https://openalex.org/W2122361470","https://openalex.org/W2163612318","https://openalex.org/W2759690896","https://openalex.org/W2984954051","https://openalex.org/W2998376881","https://openalex.org/W3156725333"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W4297676672","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W2381411913","https://openalex.org/W2381722214","https://openalex.org/W2292822667"],"abstract_inverted_index":{"Pattern":[0],"Recognition":[1],"is":[2,131,173,199,212,243,285],"an":[3],"important":[4],"way":[5],"to":[6,138,164,201,273,289],"improve":[7],"the":[8,17,22,29,35,46,58,94,98,110,129,150,155,166,176,203,206,215,223,232,239,251,256,274,277,280,295,312],"quality":[9],"of":[10,31,38,45,89,97,115,154,169,179,186,205,236,241,255,276],"life":[11],"and":[12,43,49,66,82,104,125,142,152,192,220,234,250,253,279,287,293,304,306],"promote":[13],"scientific":[14,267],"research.":[15],"Through":[16],"big":[18],"data":[19,84,281],"captured":[20],"by":[21,56,80,100],"three-axis":[23],"sensor,":[24],"this":[25,91,117,229,248,263,298],"paper":[26,52,92,118,159,264,299],"focuses":[27],"on":[28],"establishment":[30],"relevant":[32,83],"models":[33],"for":[34],"accurate":[36],"classification":[37,167,177],"19":[39],"motion":[40],"modes":[41],",":[42],"analyses":[44],"generalization":[47,95],"ability":[48,96],"overfitting.":[50],"This":[51],"establishes":[53,265],"DeepConvLSTM":[54,77,180],"model":[55,74,99,156,163,181,188,216,257,271,284,296],"combining":[57],"original":[59],"deep":[60],"learning":[61],"convolutional":[62],"neural":[63],"network":[64],"(CNN)":[65],"long-":[67],"term":[68],"short-term":[69],"memory":[70],"recursion":[71],"(LSTM).":[72],"The":[73,283],"code":[75],"about":[76],"was":[78,85,182],"written":[79],"Python":[81],"imported.":[86],"In":[87,113,261],"terms":[88,114],"methods,":[90],"evaluates":[93],"using":[101],"setaside":[102],"method":[103,107],"K-fold":[105],"cross-validation":[106],"respectively":[108],"from":[109],"algorithm":[111],"level.":[112],"indicators,":[116],"selects":[119],"accuracy,":[120,302],"accuracy":[121,151,191],"rate,":[122],"recall":[123],"rate":[124],"F1":[126],"value.":[127],"Finally,":[128],"conclusion":[130],"drawn":[132],"as":[133,245,311],"follows:":[134],"when":[135,222],"epoch":[136],"increases":[137],"40,":[139],"Train":[140],"loss":[141,144],"Val":[143],"basically":[145],"fall":[146],"together,":[147],"indicating":[148],"that":[149,175,185,214],"stability":[153,221],"are":[157,258],"excellent.The":[158],"use":[160],"logistic":[161],"regression":[162],"solve":[165],"problem":[168],"human":[170],"behavior.":[171],"It":[172],"found":[174,213],"effect":[178],"better":[183],"than":[184],"LR":[187],"with":[189],"higher":[190],"no":[193],"overfitting":[194],"phenomenon.":[195],"in":[196,247,297],"addition,":[197],"Recall":[198],"used":[200],"analyze":[202],"sensitivity":[204,219,252],"model.":[207],"After":[208,291],"several":[209],"tests,":[210],"it":[211],"shows":[217],"good":[218],"training":[224,237,242],"times":[225],"reaches":[226],"60.":[227],"On":[228],"basis,":[230],"considering":[231],"cost":[233],"efficiency":[235],"comprehensively,":[238],"number":[240],"set":[244],"60":[246],"paper,":[249],"robustness":[254,303],"both":[259],"good.":[260],"conclusion,":[262],"a":[266],"action":[268],"pattern":[269],"recognition":[270],"according":[272],"conditions":[275],"subject":[278],"given.":[282],"simple":[286],"easy":[288],"popularize.":[290],"verification":[292],"analysis,":[294],"has":[300,307],"strong":[301],"sensitivity,":[305],"certain":[308],"practical":[309],"significance":[310],"paperll.":[313]},"counts_by_year":[],"updated_date":"2026-04-17T18:11:37.981687","created_date":"2025-10-10T00:00:00"}