{"id":"https://openalex.org/W3186814128","doi":"https://doi.org/10.1109/tie.2021.3099254","title":"Learning Spatio-Temporal Representations With a Dual-Stream 3-D Residual Network for Nondriving Activity Recognition","display_name":"Learning Spatio-Temporal Representations With a Dual-Stream 3-D Residual Network for Nondriving Activity Recognition","publication_year":2021,"publication_date":"2021-07-28","ids":{"openalex":"https://openalex.org/W3186814128","doi":"https://doi.org/10.1109/tie.2021.3099254","mag":"3186814128"},"language":"en","primary_location":{"id":"doi:10.1109/tie.2021.3099254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2021.3099254","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Electronics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://dspace.lib.cranfield.ac.uk/handle/1826/16995","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057787978","display_name":"Lichao Yang","orcid":"https://orcid.org/0000-0003-0674-3123"},"institutions":[{"id":"https://openalex.org/I82284825","display_name":"Cranfield University","ror":"https://ror.org/05cncd958","country_code":"GB","type":"education","lineage":["https://openalex.org/I82284825"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Lichao Yang","raw_affiliation_strings":["School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire, U. K"],"raw_orcid":"https://orcid.org/0000-0003-0674-3123","affiliations":[{"raw_affiliation_string":"School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire, U. K","institution_ids":["https://openalex.org/I82284825"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056036277","display_name":"Xiaocai Shan","orcid":"https://orcid.org/0000-0003-0817-0357"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210126061","display_name":"Institute of Geology and Geophysics","ror":"https://ror.org/030vmwa78","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210126061"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaocai Shan","raw_affiliation_strings":["Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0817-0357","affiliations":[{"raw_affiliation_string":"Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210126061","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072073374","display_name":"Chen Lv","orcid":"https://orcid.org/0000-0001-6897-4512"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chen Lv","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"raw_orcid":"https://orcid.org/0000-0001-6897-4512","affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081460518","display_name":"James Brighton","orcid":"https://orcid.org/0000-0001-8182-6979"},"institutions":[{"id":"https://openalex.org/I82284825","display_name":"Cranfield University","ror":"https://ror.org/05cncd958","country_code":"GB","type":"education","lineage":["https://openalex.org/I82284825"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"James Brighton","raw_affiliation_strings":["School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire, U. K"],"raw_orcid":"https://orcid.org/0000-0001-8182-6979","affiliations":[{"raw_affiliation_string":"School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire, U. K","institution_ids":["https://openalex.org/I82284825"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087731729","display_name":"Yifan Zhao","orcid":"https://orcid.org/0000-0003-2383-5724"},"institutions":[{"id":"https://openalex.org/I82284825","display_name":"Cranfield University","ror":"https://ror.org/05cncd958","country_code":"GB","type":"education","lineage":["https://openalex.org/I82284825"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yifan Zhao","raw_affiliation_strings":["School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire, U. K"],"raw_orcid":"https://orcid.org/0000-0003-2383-5724","affiliations":[{"raw_affiliation_string":"School of Aerospace, Transport and Manufacturing, Cranfield University, Bedfordshire, U. K","institution_ids":["https://openalex.org/I82284825"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5057787978"],"corresponding_institution_ids":["https://openalex.org/I82284825"],"apc_list":null,"apc_paid":null,"fwci":0.7767,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73761088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"69","issue":"7","first_page":"7405","last_page":"7414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9970999956130981,"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":0.9883999824523926,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7720530033111572},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7688430547714233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6491438746452332},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6171507835388184},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5814149379730225},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5653865933418274},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5145065784454346},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.46942833065986633},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.4526507556438446},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.42266660928726196},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3936137557029724}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7720530033111572},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7688430547714233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6491438746452332},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6171507835388184},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5814149379730225},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5653865933418274},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5145065784454346},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.46942833065986633},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.4526507556438446},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.42266660928726196},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3936137557029724},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tie.2021.3099254","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tie.2021.3099254","pdf_url":null,"source":{"id":"https://openalex.org/S58031724","display_name":"IEEE Transactions on Industrial Electronics","issn_l":"0278-0046","issn":["0278-0046","1557-9948"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Electronics","raw_type":"journal-article"},{"id":"pmh:oai:dspace.lib.cranfield.ac.uk:1826/16995","is_oa":true,"landing_page_url":"https://dspace.lib.cranfield.ac.uk/handle/1826/16995","pdf_url":null,"source":{"id":"https://openalex.org/S4306401778","display_name":"CERES (Cranfield University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I82284825","host_organization_name":"Cranfield University","host_organization_lineage":["https://openalex.org/I82284825"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"pmh:oai:dspace.lib.cranfield.ac.uk:1826/16995","is_oa":true,"landing_page_url":"https://dspace.lib.cranfield.ac.uk/handle/1826/16995","pdf_url":null,"source":{"id":"https://openalex.org/S4306401778","display_name":"CERES (Cranfield University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I82284825","host_organization_name":"Cranfield University","host_organization_lineage":["https://openalex.org/I82284825"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"},"sustainable_development_goals":[{"score":0.4300000071525574,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[{"id":"https://openalex.org/G8465379673","display_name":null,"funder_award_id":"EP/N012089/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1522734439","https://openalex.org/W1983364832","https://openalex.org/W2016053056","https://openalex.org/W2126579184","https://openalex.org/W2156303437","https://openalex.org/W2194775991","https://openalex.org/W2340043522","https://openalex.org/W2616247523","https://openalex.org/W2722459813","https://openalex.org/W2765793020","https://openalex.org/W2778498877","https://openalex.org/W2809822040","https://openalex.org/W2896950454","https://openalex.org/W2900471873","https://openalex.org/W2901473640","https://openalex.org/W2902178419","https://openalex.org/W2912346386","https://openalex.org/W2934625602","https://openalex.org/W2944843851","https://openalex.org/W2963155035","https://openalex.org/W2963524571","https://openalex.org/W2963616706","https://openalex.org/W2963820951","https://openalex.org/W2971387592","https://openalex.org/W2973218919","https://openalex.org/W2992457155","https://openalex.org/W3027225766","https://openalex.org/W3040077947","https://openalex.org/W3102564565","https://openalex.org/W3146689237","https://openalex.org/W4242994874","https://openalex.org/W4301712968","https://openalex.org/W6600983433","https://openalex.org/W6631043569","https://openalex.org/W6638667902","https://openalex.org/W6677995690","https://openalex.org/W6682864246"],"related_works":["https://openalex.org/W3196952692","https://openalex.org/W2984708981","https://openalex.org/W4300939921","https://openalex.org/W4383097772","https://openalex.org/W2964350391","https://openalex.org/W2274287116","https://openalex.org/W3213976941","https://openalex.org/W2897517148","https://openalex.org/W2967403871","https://openalex.org/W2983358626"],"abstract_inverted_index":{"Accurate":[0],"recognition":[1,54,82],"of":[2,11,33,75,96,117,122,180],"nondriving":[3],"activity":[4,81],"(NDA)":[5],"is":[6,89,110],"important":[7],"for":[8,140],"the":[9,25,46,73,80,94,127,141,144,164,169,173,178,181,185],"design":[10],"intelligent":[12],"human":[13],"machine":[14],"interface":[15],"to":[16,45,71,91,113],"achieve":[17],"a":[18,43,61,85],"smooth":[19],"and":[20,39,78,100,119,130],"safe":[21],"control":[22],"transition":[23],"in":[24,168],"conditionally":[26],"automated":[27],"driving":[28,123],"vehicle.":[29],"However,":[30],"some":[31],"characteristics":[32],"such":[34],"activities":[35],"like":[36],"limited-extent":[37],"movement":[38],"similar":[40],"background":[41],"pose":[42],"challenge":[44],"existing":[47],"3-D":[48,63],"convolutional":[49],"neural":[50],"network":[51,69],"based":[52,125],"action":[53],"methods.":[55,159],"In":[56],"this":[57,161],"article,":[58],"we":[59],"propose":[60],"dual-stream":[62],"residual":[64,68],"network,":[65],"named":[66],"DS3D":[67,146],"(ResNet),":[70],"enhance":[72],"learning":[74,95],"spatio-temporal":[76,165],"representation":[77,99],"improve":[79],"performance.":[83],"Specifically,":[84],"parallel":[86],"two-stream":[87],"structure":[88],"introduced":[90],"focus":[92],"on":[93,126,184],"short-time":[97],"spatial":[98],"small-region":[101],"temporal":[102],"representation.":[103],"A":[104,133],"two-feed":[105],"driver":[106],"behavior":[107,124],"monitoring":[108],"framework":[109],"further":[111],"build":[112],"classify":[114],"four":[115],"types":[116,121],"NDAs":[118],"two":[120],"driver's":[128],"head":[129],"hand":[131],"movement.":[132],"novel":[134],"NDA":[135],"dataset":[136],"has":[137],"been":[138],"constructed":[139],"evaluation,":[142],"where":[143],"proposed":[145,182],"ResNet":[147],"achieves":[148],"83.35%":[149],"average":[150],"accuracy,":[151],"at":[152],"least":[153],"5%":[154],"above":[155],"three":[156],"selected":[157,186],"state-of-the-art":[158],"Furthermore,":[160],"study":[162],"investigates":[163],"features":[166],"learned":[167],"hidden":[170],"layer":[171],"through":[172],"saliency":[174],"map,":[175],"which":[176],"explains":[177],"superiority":[179],"model":[183],"NDAs.":[187]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
