乐胖代购免代理版

{"id":"https://openalex.org/W3098983911","doi":"https://doi.org/10.1109/mhs48134.2019.9249255","title":"Fusion system of vision and hearing sensation using Deep Learning Fusion system of vision and hearing sensation using Deep Learning","display_name":"Fusion system of vision and hearing sensation using Deep Learning Fusion system of vision and hearing sensation using Deep Learning","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3098983911","doi":"https://doi.org/10.1109/mhs48134.2019.9249255","mag":"3098983911"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/mhs48134.2019.9249255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5046065044","display_name":"Kazuto Tsumura","orcid":null},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuto Tsumura","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University 1\u20131 Rokkodai-cho, Nada-ku, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University 1\u20131 Rokkodai-cho, Nada-ku, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088292486","display_name":"Futoshi Kobayashi","orcid":"https://orcid.org/0000-0002-4663-6448"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Futoshi Kobayashi","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University 1\u20131 Rokkodai-cho, Nada-ku, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University 1\u20131 Rokkodai-cho, Nada-ku, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064765751","display_name":"Hiroyuki Nakamoto","orcid":"https://orcid.org/0000-0001-8259-9317"},"institutions":[{"id":"https://openalex.org/I65837984","display_name":"Kobe University","ror":"https://ror.org/03tgsfw79","country_code":"JP","type":"funder","lineage":["https://openalex.org/I65837984"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroyuki Nakamoto","raw_affiliation_strings":["Graduate School of System Informatics, Kobe University 1\u20131 Rokkodai-cho, Nada-ku, Kobe, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of System Informatics, Kobe University 1\u20131 Rokkodai-cho, Nada-ku, Kobe, Japan","institution_ids":["https://openalex.org/I65837984"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":61},"biblio":{"volume":"69","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9731,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13382","display_name":"Robotics and Automated Systems","score":0.9731,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9564,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9551,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/sensor-fusion","display_name":"Sensor Fusion","score":0.6662301},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5969261}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7410874},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7102697},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6980133},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.6662301},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5969261},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5682064},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5135746},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.50655687},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.50038767},{"id":"https://openalex.org/C94487597","wikidata":"https://www.wikidata.org/wiki/Q11101","display_name":"Sensory system","level":2,"score":0.4675117},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3556226},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/mhs48134.2019.9249255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":7,"referenced_works":["https://openalex.org/W1597614728","https://openalex.org/W1836465849","https://openalex.org/W2091987367","https://openalex.org/W2112796928","https://openalex.org/W2744582249","https://openalex.org/W2912340236","https://openalex.org/W302761957"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4321487865","https://openalex.org/W4312417841","https://openalex.org/W4293226380","https://openalex.org/W4226493464","https://openalex.org/W3133861977","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2951211570","https://openalex.org/W2611989081"],"abstract_inverted_index":{"Recently,":[0],"sensing":[1],"technology":[2,26],"has":[3],"been":[4,16],"dramatically":[5],"developed.":[6],"Along":[7],"with":[8],"this,":[9],"a":[10,19,38,41,51,124,144],"wide":[11],"variety":[12],"of":[13,35,81,111],"sensors":[14,36,49],"have":[15],"used":[17],"in":[18,37,71,89,105],"single":[20],"system":[21,39,116,145],"such":[22,74,112],"as":[23,32,75],"automated":[24],"driving":[25],"and":[27,69,78,99,136,150,155,168,179,182],"the":[28,33,48,59,63,76,82,86,90,96,138,184,188,193],"robot":[29],"industry.":[30],"However,":[31],"number":[34],"increases,":[40],"fusion":[42,101,108,115,137,163,192],"method":[43,125],"for":[44,133,177],"information":[45,56,60,87,100,181],"obtained":[46,61],"from":[47,57,62],"becomes":[50],"problem.":[52],"When":[53],"humans":[54],"recognize":[55],"environment,":[58],"five":[64],"senses":[65],"is":[66,93,102,117],"once":[67],"transmitted":[68,94],"processed":[70,88],"sensory":[72,91],"areas":[73,80],"visual":[77,154,178],"auditory":[79,156,180],"brain.":[83],"After":[84],"that,":[85],"area":[92],"to":[95,126,160,187],"association":[97],"area,":[98],"performed.":[103],"Also":[104],"robot's":[106],"sensor":[107,114,135,162],"system,":[109,143],"development":[110],"human":[113],"expected.":[118],"In":[119,141],"this":[120,142],"paper,":[121],"we":[122],"propose":[123],"extract":[127],"feature":[128,139,166],"value":[129,167],"using":[130,153,171],"deep":[131],"learning":[132],"each":[134],"value.":[140],"constructed":[146],"by":[147,164],"combining":[148],"lipreading":[149],"speech":[151],"recognition":[152,185,194],"information.":[157],"We":[158],"aim":[159],"realize":[161],"extracting":[165],"recognizing":[169],"words":[170],"Convolutional":[172],"Neural":[173,189],"Network":[174,190],"(CNN)":[175],"respectively":[176],"inputting":[183],"results":[186],"that":[191],"results.":[195]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3098983911","counts_by_year":[],"updated_date":"2025-02-02T11:46:25.356421","created_date":"2020-11-23"}