{"id":"https://openalex.org/W4304084247","doi":"https://doi.org/10.1145/3503161.3548310","title":"Image-Signal Correlation Network for Textile Fiber Identification","display_name":"Image-Signal Correlation Network for Textile Fiber Identification","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304084247","doi":"https://doi.org/10.1145/3503161.3548310"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548310","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548310","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","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/A5101685717","display_name":"Bo Peng","orcid":"https://orcid.org/0000-0003-1514-6881"},"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":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"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":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062696252","display_name":"Yining Qiu","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":"Yining Qiu","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103200805","display_name":"Dong Wu","orcid":"https://orcid.org/0000-0002-2306-5769"},"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":"Wu Dong","raw_affiliation_strings":["Fudan University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","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":["Fudan University &amp; Zhongshan PoolNet Technology Ltd, Shanghai &amp; Zhongshan, China"],"affiliations":[{"raw_affiliation_string":"Fudan University &amp; Zhongshan PoolNet Technology Ltd, Shanghai &amp; Zhongshan, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101685717"],"corresponding_institution_ids":["https://openalex.org/I24943067"],"apc_list":null,"apc_paid":null,"fwci":1.0366,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70942228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3848","last_page":"3856"},"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":0.9976999759674072,"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":0.9976999759674072,"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/T11666","display_name":"Color Science and Applications","score":0.9850999712944031,"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"}},{"id":"https://openalex.org/T11595","display_name":"Textile materials and evaluations","score":0.9678999781608582,"subfield":{"id":"https://openalex.org/subfields/2507","display_name":"Polymers and Plastics"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.6978065967559814},{"id":"https://openalex.org/keywords/fiber","display_name":"Fiber","score":0.6609468460083008},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6173939108848572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5587791800498962},{"id":"https://openalex.org/keywords/textile","display_name":"Textile","score":0.4641522169113159},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.46299582719802856},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.45491480827331543},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4488737881183624},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4348217248916626},{"id":"https://openalex.org/keywords/microscope","display_name":"Microscope","score":0.42820537090301514},{"id":"https://openalex.org/keywords/absorption","display_name":"Absorption (acoustics)","score":0.41814762353897095},{"id":"https://openalex.org/keywords/near-infrared-spectroscopy","display_name":"Near-infrared spectroscopy","score":0.4127236306667328},{"id":"https://openalex.org/keywords/biological-system","display_name":"Biological system","score":0.40969330072402954},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.39911729097366333},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.30054205656051636},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1442461609840393},{"id":"https://openalex.org/keywords/composite-material","display_name":"Composite material","score":0.08257341384887695}],"concepts":[{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.6978065967559814},{"id":"https://openalex.org/C519885992","wikidata":"https://www.wikidata.org/wiki/Q161","display_name":"Fiber","level":2,"score":0.6609468460083008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6173939108848572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5587791800498962},{"id":"https://openalex.org/C164767435","wikidata":"https://www.wikidata.org/wiki/Q28823","display_name":"Textile","level":2,"score":0.4641522169113159},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.46299582719802856},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.45491480827331543},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4488737881183624},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4348217248916626},{"id":"https://openalex.org/C67649825","wikidata":"https://www.wikidata.org/wiki/Q196538","display_name":"Microscope","level":2,"score":0.42820537090301514},{"id":"https://openalex.org/C125287762","wikidata":"https://www.wikidata.org/wiki/Q1758948","display_name":"Absorption (acoustics)","level":2,"score":0.41814762353897095},{"id":"https://openalex.org/C43571822","wikidata":"https://www.wikidata.org/wiki/Q599037","display_name":"Near-infrared spectroscopy","level":2,"score":0.4127236306667328},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.40969330072402954},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.39911729097366333},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.30054205656051636},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1442461609840393},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.08257341384887695},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3503161.3548310","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548310","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.4699999988079071,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1966649791","https://openalex.org/W2012592962","https://openalex.org/W2052684391","https://openalex.org/W2113543997","https://openalex.org/W2123787746","https://openalex.org/W2194775991","https://openalex.org/W2383864372","https://openalex.org/W2400417223","https://openalex.org/W2886042776","https://openalex.org/W2888396224","https://openalex.org/W2963852396","https://openalex.org/W2981663434","https://openalex.org/W2984700939","https://openalex.org/W2984971137","https://openalex.org/W2999072242","https://openalex.org/W3010867338","https://openalex.org/W3016138882","https://openalex.org/W3028000844","https://openalex.org/W3034203210","https://openalex.org/W3173549566","https://openalex.org/W3182718171","https://openalex.org/W4283464209","https://openalex.org/W4293768955"],"related_works":["https://openalex.org/W2022634505","https://openalex.org/W3193374793","https://openalex.org/W2799955745","https://openalex.org/W2166083489","https://openalex.org/W2273602677","https://openalex.org/W2891307765","https://openalex.org/W1558185205","https://openalex.org/W2047422789","https://openalex.org/W3032189291","https://openalex.org/W3183273387"],"abstract_inverted_index":{"Identifying":[0],"fiber":[1,25,107,124,185,195,227,261],"compositions":[2,38],"is":[3,70,213],"an":[4,135],"important":[5],"aspect":[6],"of":[7,24,54,76,103,161,169,179,193,200,224,252],"the":[8,21,36,40,44,52,58,62,81,98,118,130,154,164,170,175,190,194,197,201,210,217,221,225,249],"textile":[9,92,123,184,260],"industry.":[10],"In":[11,113],"recent":[12],"decades,":[13],"near-infrared":[14],"spectroscopy":[15],"has":[16],"shown":[17],"its":[18],"potential":[19,251],"in":[20],"automatic":[22],"detection":[23],"components.":[26],"However,":[27],"for":[28,182,259],"plant":[29],"fibers":[30,104,203],"such":[31],"as":[32],"cotton":[33],"and":[34,42,68,140,145,209,235,245,256],"linen,":[35],"chemical":[37],"are":[39,47,204,238],"same":[41,59,63],"thus":[43],"absorption":[45,166],"spectra":[46],"very":[48],"similar,":[49],"leading":[50],"to":[51,79,84,105,151,173,215,219,242],"problem":[53],"\"different":[55],"materials":[56],"with":[57,65,109,163],"spectrum,":[60],"whereas":[61],"material":[64],"different":[66],"spectrums\"":[67],"it":[69],"difficult":[71],"using":[72],"a":[73,95,110,230],"single":[74,244],"mode":[75],"NIR":[77,120,171,222,257],"signals":[78,223,258],"capture":[80,174],"effective":[82],"features":[83,156,178],"distinguish":[85],"these":[86],"fibers.":[87],"To":[88,187],"solve":[89],"this":[90,114],"problem,":[91],"experts":[93],"under":[94],"microscope":[96],"measure":[97],"cross-sectional":[99],"or":[100],"longitudinal":[101],"characteristics":[102,192],"determine":[106],"contents":[108],"destructive":[111],"way.":[112],"paper,":[115],"we":[116,133],"construct":[117],"first":[119],"signal-microscope":[121],"image":[122],"composition":[125,262],"dataset":[126],"(NIRITFC).":[127],"Based":[128],"on":[129],"NIRITFC":[131],"dataset,":[132],"propose":[134],"image-signal":[136,142,146],"correlation":[137,143,147],"network":[138],"(ISiC-Net)":[139],"design":[141],"perception":[144],"attention":[148],"modules,":[149],"respectively,":[150],"effectively":[152],"integrate":[153],"visual":[155],"(esp.":[157],"local":[158],"texture":[159],"details":[160],"fibers)":[162],"finer":[165],"spectrum":[167],"information":[168],"signal":[172],"deep":[176],"abstract":[177],"bimodal":[180,246],"data":[181],"nondestructive":[183],"identification.":[186,263],"better":[188],"learn":[189],"spectral":[191],"components,":[196],"endmember":[198],"vectors":[199],"corresponding":[202,226],"generated":[205],"by":[206,229],"embedding":[207],"encoding,":[208],"reconstruction":[211],"loss":[212],"designed":[214],"guide":[216],"model":[218],"reconstruct":[220],"components":[228],"nonlinear":[231],"mapping.":[232],"The":[233],"quantitative":[234],"qualitative":[236],"results":[237],"significantly":[239],"improved":[240],"compared":[241],"both":[243],"approaches,":[247],"indicating":[248],"great":[250],"combining":[253],"microscopic":[254],"images":[255]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-04-23T09:07:50.710637","created_date":"2025-10-10T00:00:00"}
