{"id":"https://openalex.org/W4372260702","doi":"https://doi.org/10.1109/icassp49357.2023.10097205","title":"A Multi-Signal Perception Network for Textile Composition Identification","display_name":"A Multi-Signal Perception Network for Textile Composition Identification","publication_year":2023,"publication_date":"2023-05-05","ids":{"openalex":"https://openalex.org/W4372260702","doi":"https://doi.org/10.1109/icassp49357.2023.10097205"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49357.2023.10097205","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10097205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5067952051","display_name":"Bo Peng","orcid":"https://orcid.org/0000-0003-4183-5939"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Peng","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001357812","display_name":"Liren He","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liren He","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101729367","display_name":"Dong Wu","orcid":"https://orcid.org/0000-0002-8018-5548"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Wu","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057267422","display_name":"Mingmin Chi","orcid":null},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingmin Chi","raw_affiliation_strings":["Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","Zhongshan Fudan Joint Innovation Center, Zhongshan PoolNet Technology Co., Ltd, Zhongshan, China","School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","Zhengzhou Zhongke Institute of Integrated Circuit and System Application"],"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Data Science, Fudan University,School of Computer Science,Shanghai,China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Zhongshan Fudan Joint Innovation Center, Zhongshan PoolNet Technology Co., Ltd, Zhongshan, China","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science, Shanghai Key Laboratory of Data Science, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Zhengzhou Zhongke Institute of Integrated Circuit and System Application","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081445509","display_name":"Jintao Chen","orcid":"https://orcid.org/0000-0003-2299-8820"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jintao Chen","raw_affiliation_strings":["Shanghai Fabric Eyes Artificial Intelligence Technology Co., Ltd,Shanghai,China","Shanghai Fabric Eyes Artificial Intelligence Technology Co., Ltd, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Fabric Eyes Artificial Intelligence Technology Co., Ltd,Shanghai,China","institution_ids":["https://openalex.org/I4210100255"]},{"raw_affiliation_string":"Shanghai Fabric Eyes Artificial Intelligence Technology Co., Ltd, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5067952051"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07438408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"30","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9958000183105469,"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"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9958000183105469,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6986082196235657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6168121099472046},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5811508297920227},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.5274244546890259},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5220280289649963},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5007596015930176},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4820869266986847},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4799244999885559},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4542127847671509},{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.45142027735710144},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44628801941871643},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4136075973510742}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6986082196235657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6168121099472046},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5811508297920227},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.5274244546890259},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5220280289649963},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5007596015930176},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4820869266986847},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4799244999885559},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4542127847671509},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.45142027735710144},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44628801941871643},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4136075973510742},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49357.2023.10097205","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icassp49357.2023.10097205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1909952827","https://openalex.org/W1966649791","https://openalex.org/W2052684391","https://openalex.org/W2383864372","https://openalex.org/W2400417223","https://openalex.org/W2551396370","https://openalex.org/W2566365295","https://openalex.org/W2795340004","https://openalex.org/W2886042776","https://openalex.org/W2954214015","https://openalex.org/W2963190516","https://openalex.org/W2963852396","https://openalex.org/W2984700939","https://openalex.org/W2994661265","https://openalex.org/W3010867338","https://openalex.org/W3016138882","https://openalex.org/W3028000844","https://openalex.org/W3094502228","https://openalex.org/W3137646246","https://openalex.org/W3174906557","https://openalex.org/W3182718171","https://openalex.org/W3212942095","https://openalex.org/W4283464209","https://openalex.org/W4293519349","https://openalex.org/W4304084247","https://openalex.org/W4385245566","https://openalex.org/W6710258478","https://openalex.org/W6729654139","https://openalex.org/W6771945487","https://openalex.org/W6784333009","https://openalex.org/W6797613833","https://openalex.org/W6803076157"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4256502920","https://openalex.org/W4382701072"],"abstract_inverted_index":{"Textile":[0],"composition":[1,66],"identification":[2],"(TCI)":[3],"is":[4,85,129],"an":[5],"essential":[6],"basic":[7],"link":[8],"in":[9],"the":[10,27,36,46,69,74,102,109,113,150],"textile":[11,65],"industry.":[12],"Methods":[13],"based":[14],"on":[15],"computer":[16],"vision":[17],"or":[18],"near-infrared":[19],"(NIR)":[20],"signal":[21,97,137],"processing":[22],"have":[23],"shown":[24],"potential":[25],"for":[26,63],"nondestructive":[28,64],"TCI":[29],"task.":[30],"However,":[31],"these":[32],"methods":[33],"ignore":[34],"that":[35],"integration":[37],"of":[38,76,112,149],"NIR":[39],"signals":[40],"and":[41,140,146,160],"visual":[42],"information":[43,53,135],"may":[44],"help":[45],"model":[47,70],"learn":[48],"a":[49,58,80,95,118,125],"better":[50],"representation":[51],"through":[52],"complementarity.":[54],"This":[55],"paper":[56],"propose":[57,94],"Multi-Signal":[59],"Perception":[60],"Network":[61],"(MSPNet)":[62],"identification,":[67],"allowing":[68],"to":[71,87,100,131,138,142,157],"benefit":[72],"from":[73,136],"advantages":[75],"multimodal":[77,96,106,161],"data.":[78,107],"Firstly,":[79],"two-way":[81],"feature":[82],"extraction":[83],"network":[84],"used":[86],"obtain":[88],"multi-modal":[89],"features.":[90],"After":[91],"that,":[92],"we":[93],"fusion":[98],"module":[99,122],"control":[101],"aggregation":[103,127],"granularity":[104],"among":[105],"Specifically,":[108],"target":[110,119],"areas":[111],"image":[114,139,141],"are":[115,153],"perceived":[116],"by":[117],"area":[120],"perception":[121],"(TAP).":[123],"Then":[124],"bi-gated":[126],"(Bi-GFA)":[128],"designed":[130],"capture":[132],"consistent":[133],"semantic":[134],"signal.":[143],"The":[144],"quantitative":[145],"qualitative":[147],"results":[148],"proposed":[151],"MSPNet":[152],"significantly":[154],"improved":[155],"compared":[156],"both":[158],"single":[159],"approaches.":[162]},"counts_by_year":[],"updated_date":"2025-12-24T23:09:58.560324","created_date":"2025-10-10T00:00:00"}
