{"id":"https://openalex.org/W4393065949","doi":"https://doi.org/10.1109/rivf60135.2023.10471852","title":"Dual-Stream Deep Neural Network with Learnable Fusion Weights for 3D Object Detection and Recognition","display_name":"Dual-Stream Deep Neural Network with Learnable Fusion Weights for 3D Object Detection and Recognition","publication_year":2023,"publication_date":"2023-12-23","ids":{"openalex":"https://openalex.org/W4393065949","doi":"https://doi.org/10.1109/rivf60135.2023.10471852"},"language":"en","primary_location":{"id":"doi:10.1109/rivf60135.2023.10471852","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/rivf60135.2023.10471852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 RIVF International Conference on Computing and Communication Technologies (RIVF)","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/A5075750194","display_name":"Oscal T.\u2010C. Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Oscal T.-C. Chen","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076499498","display_name":"Yu-Wei Jhao","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yu-Wei Jhao","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074819260","display_name":"Chih-Yu Chung","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chih-Yu Chung","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100586957","display_name":"Yue-Han Li","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Yue-Han Li","raw_affiliation_strings":["National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Electrical Engineering,Chiayi,Taiwan,62102","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019938778","display_name":"Manh-Hung Ha","orcid":"https://orcid.org/0000-0002-5782-6829"},"institutions":[{"id":"https://openalex.org/I177233841","display_name":"Vietnam National University, Hanoi","ror":"https://ror.org/02jmfj006","country_code":"VN","type":"education","lineage":["https://openalex.org/I177233841"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Manh-Hung Ha","raw_affiliation_strings":["Int'l School, Vietnam National University,Faculty of Applied Sciences,Hanoi,Vietnam,100000"],"affiliations":[{"raw_affiliation_string":"Int'l School, Vietnam National University,Faculty of Applied Sciences,Hanoi,Vietnam,100000","institution_ids":["https://openalex.org/I177233841"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5075750194"],"corresponding_institution_ids":["https://openalex.org/I148099254"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21384356,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"260","last_page":"265"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9404000043869019,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9404000043869019,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9121000170707703,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6572024822235107},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6498316526412964},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6226056814193726},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5593351721763611},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5566645860671997},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5269982218742371},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.46746376156806946},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.46727052330970764},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4594884514808655},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4424492120742798}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6572024822235107},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6498316526412964},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6226056814193726},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5593351721763611},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5566645860671997},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5269982218742371},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.46746376156806946},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.46727052330970764},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4594884514808655},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4424492120742798},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rivf60135.2023.10471852","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/rivf60135.2023.10471852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 RIVF International Conference on Computing and Communication Technologies (RIVF)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7428988112","display_name":null,"funder_award_id":"MOST 111-2221-E-194-054","funder_id":"https://openalex.org/F4320309618","funder_display_name":"Ministry of Science and Technology"}],"funders":[{"id":"https://openalex.org/F4320309618","display_name":"Ministry of Science and Technology","ror":"https://ror.org/02b207r52"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2949708697","https://openalex.org/W2963351448","https://openalex.org/W2963416674","https://openalex.org/W2963727135","https://openalex.org/W2968296999","https://openalex.org/W3035574168","https://openalex.org/W3105073457","https://openalex.org/W3118479569","https://openalex.org/W3176740453","https://openalex.org/W4308068354","https://openalex.org/W4310269208","https://openalex.org/W6739778489","https://openalex.org/W6760424586","https://openalex.org/W6763422710"],"related_works":["https://openalex.org/W2114275278","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W1489511283","https://openalex.org/W4387272257","https://openalex.org/W2769899322","https://openalex.org/W2974914859","https://openalex.org/W2026565050","https://openalex.org/W2110244802","https://openalex.org/W949345935"],"abstract_inverted_index":{"To":[0],"enable":[1],"effective":[2],"obstacle":[3],"avoidance":[4],"in":[5,26,64,197],"autonomous":[6],"vehicles,":[7],"3D":[8,24,209],"object":[9,210],"detection":[10,211],"and":[11,37,44,61,98,100,177,212],"recognition":[12],"play":[13],"a":[14,71,116,187],"crucial":[15],"role.":[16],"Currently,":[17],"there":[18],"are":[19,148],"various":[20],"models":[21],"for":[22,174,179,208],"perceiving":[23],"objects":[25],"the":[27,55,79,92,101,123,136,141,155,159,201,204],"environment,":[28],"utilizing":[29],"multiple":[30],"sensors":[31,60],"such":[32],"as":[33],"RGB":[34],"cameras,":[35],"LiDAR,":[36],"radar.":[38],"Each":[39],"sensor":[40],"has":[41],"its":[42],"advantages":[43],"disadvantages.":[45],"The":[46,87,133],"objective":[47],"of":[48,91,135,158,172,190,203],"this":[49],"study":[50],"is":[51],"to":[52,114,121,150],"effectively":[53],"integrate":[54],"data":[56,94,103,185],"from":[57,95],"these":[58],"three":[59],"process":[62],"them":[63],"an":[65,109,167],"integrated":[66,93],"manner.":[67],"Thus,":[68],"we":[69,162],"propose":[70,108],"dual-stream":[72,206],"Deep":[73],"Neural":[74],"Network":[75],"(DNN)":[76],"based":[77],"on":[78],"modified":[80],"VoxelNet,":[81],"achieved":[82,163],"through":[83,140],"neural":[84],"architecture":[85],"search.":[86],"two":[88,137],"streams":[89,138],"consist":[90],"imager,":[96],"LiDAR":[97,102],"radar,":[99],"with":[104,166,186],"depth":[105,111,118,131],"completion.":[106],"We":[107],"improved":[110],"completion":[112],"technique":[113],"generate":[115],"dense":[117],"map,":[119],"aiming":[120],"address":[122],"point":[124],"cloud's":[125],"boundary":[126],"blurring":[127],"issues":[128],"introduced":[129],"by":[130],"inpainting.":[132],"fusion":[134,146],"occurs":[139],"cost":[142],"function,":[143],"where":[144],"learnable":[145],"weights":[147],"employed":[149],"achieve":[151],"outstanding":[152],"performance.":[153],"In":[154],"validation":[156],"set":[157],"nuScenes":[160],"dataset,":[161],"remarkable":[164],"results,":[165],"average":[168],"precision":[169],"(AP)":[170],"score":[171],"61.9%":[173],"car":[175],"classification":[176],"47.5%":[178],"pedestrian":[180],"classification,":[181],"solely":[182],"using":[183],"frontview":[184],"77-degree":[188],"field":[189],"view.":[191],"These":[192],"scores":[193],"surpass":[194],"those":[195],"reported":[196],"previous":[198],"literature,":[199],"highlighting":[200],"effectiveness":[202],"proposed":[205],"DNN":[207],"recognition.":[213]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}