{"id":"https://openalex.org/W7225205223","doi":"https://doi.org/10.1111/cote.70123","title":"Spectral reflectance reconstruction via extreme learning machine: Cross\u2010dataset evaluation and generalisation analysis","display_name":"Spectral reflectance reconstruction via extreme learning machine: Cross\u2010dataset evaluation and generalisation analysis","publication_year":2026,"publication_date":"2026-11-02","ids":{"openalex":"https://openalex.org/W7225205223","doi":"https://doi.org/10.1111/cote.70123"},"language":"en","primary_location":{"id":"doi:10.1111/cote.70123","doi":"https://doi.org/10.1111/cote.70123","is_oa":true,"landing_page_url":"https://doi.org/10.1111/cote.70123","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cote.70123","source":{"id":"https://openalex.org/S78419349","display_name":"Coloration Technology","issn_l":"1472-3581","issn":["1472-3581","1478-4408"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Coloration Technology","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cote.70123","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5030911150","display_name":"Zhitong Xing","orcid":"https://orcid.org/0000-0001-7253-1220","observed_orcids":["https://orcid.org/0000-0001-7253-1220"]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhitong Xing","raw_affiliation_strings":["College of Chemistry and Chemical Engineering Donghua University  Shanghai China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Chemical Engineering Donghua University  Shanghai China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160442185","display_name":"Chenfei Han","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenfei Han","raw_affiliation_strings":["College of Chemistry and Chemical Engineering Donghua University  Shanghai China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Chemistry and Chemical Engineering Donghua University  Shanghai China","institution_ids":["https://openalex.org/I181326427"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100786259","display_name":"Rong Li","orcid":"https://orcid.org/0000-0003-1402-9042","observed_orcids":["https://orcid.org/0000-0003-1402-9042"]},"institutions":[{"id":"https://openalex.org/I181326427","display_name":"Donghua University","ror":"https://ror.org/035psfh38","country_code":"CN","type":"education","lineage":["https://openalex.org/I181326427"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rong Li","raw_affiliation_strings":["College of Chemistry and Chemical Engineering Donghua University  Shanghai China"],"raw_orcid":"https://orcid.org/0000-0003-1402-9042","affiliations":[{"raw_affiliation_string":"College of Chemistry and Chemical Engineering Donghua University  Shanghai China","institution_ids":["https://openalex.org/I181326427"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100786259"],"corresponding_institution_ids":["https://openalex.org/I181326427"],"apc_list":{"value":3950,"currency":"USD","value_usd":3950},"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.77519692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9965999722480774,"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/T12676","display_name":"Machine Learning and ELM","score":0.0017000000225380063,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.0003000000142492354,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/spectral-reflectance-reconstruction","display_name":"spectral reflectance reconstruction","score":0.9909999966621399},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"extreme learning machine","score":0.9950000047683716},{"id":"https://openalex.org/keywords/cross-dataset-generalization","display_name":"cross-dataset generalization","score":0.8769999742507935},{"id":"https://openalex.org/keywords/colour-difference","display_name":"color difference","score":0.4959999918937683},{"id":"https://openalex.org/keywords/spectral-angle","display_name":"spectral angle","score":0.4869999885559082},{"id":"https://openalex.org/keywords/radial-basis-functions","display_name":"radial basis functions","score":0.5619999766349792},{"id":"https://openalex.org/keywords/neural-network-comparison","display_name":"neural network comparison","score":0.42800000309944153}],"concepts":[{"id":"https://openalex.org/C129112856","wikidata":"https://www.wikidata.org/wiki/Q375479","display_name":"Standard illuminant","level":2,"score":0.7613000273704529},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7239000201225281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5975000262260437},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5939000248908997},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5097000002861023},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.5081999897956848},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4945000112056732},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4542999863624573},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.4440000057220459},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4422999918460846},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4041999876499176},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.35839998722076416},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.35260000824928284},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.30559998750686646},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.3052000105381012},{"id":"https://openalex.org/C152822103","wikidata":"https://www.wikidata.org/wiki/Q7575207","display_name":"Spectral shape analysis","level":3,"score":0.299699991941452},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C6260449","wikidata":"https://www.wikidata.org/wiki/Q41364","display_name":"Wavelength","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C128990827","wikidata":"https://www.wikidata.org/wiki/Q192830","display_name":"Coefficient of determination","level":2,"score":0.2919999957084656},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.27790001034736633},{"id":"https://openalex.org/C180690934","wikidata":"https://www.wikidata.org/wiki/Q25377588","display_name":"Stellar classification","level":3,"score":0.2766999900341034},{"id":"https://openalex.org/C167085575","wikidata":"https://www.wikidata.org/wiki/Q6803654","display_name":"Mean squared prediction error","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.2524999976158142}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1111/cote.70123","doi":"https://doi.org/10.1111/cote.70123","is_oa":true,"landing_page_url":"https://doi.org/10.1111/cote.70123","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cote.70123","source":{"id":"https://openalex.org/S78419349","display_name":"Coloration Technology","issn_l":"1472-3581","issn":["1472-3581","1478-4408"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Coloration Technology","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1111/cote.70123","doi":"https://doi.org/10.1111/cote.70123","is_oa":true,"landing_page_url":"https://doi.org/10.1111/cote.70123","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/cote.70123","source":{"id":"https://openalex.org/S78419349","display_name":"Coloration Technology","issn_l":"1472-3581","issn":["1472-3581","1478-4408"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-40","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Coloration Technology","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7225205223.pdf","grobid_xml":"https://content.openalex.org/works/W7225205223.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W2000512760","https://openalex.org/W2020434162","https://openalex.org/W2069300393","https://openalex.org/W2138383519","https://openalex.org/W2150969685","https://openalex.org/W2516746652","https://openalex.org/W2756495163","https://openalex.org/W2964649059","https://openalex.org/W2985260632","https://openalex.org/W2993978288","https://openalex.org/W3011404321","https://openalex.org/W4297539661","https://openalex.org/W4313889603","https://openalex.org/W4316369087","https://openalex.org/W4323926221","https://openalex.org/W4324093190","https://openalex.org/W4362731426","https://openalex.org/W4366774634","https://openalex.org/W4372203465","https://openalex.org/W4377996608","https://openalex.org/W4377997206","https://openalex.org/W4383912808","https://openalex.org/W4386374350","https://openalex.org/W4387746090","https://openalex.org/W4396505468","https://openalex.org/W4399362717","https://openalex.org/W4400683461","https://openalex.org/W4403083212","https://openalex.org/W4415293267","https://openalex.org/W7134254296"],"related_works":["https://openalex.org/W2069300393","https://openalex.org/W3081309737","https://openalex.org/W254505296","https://openalex.org/W2614584450","https://openalex.org/W4323926221","https://openalex.org/W2211722660","https://openalex.org/W4390502154","https://openalex.org/W2280289986","https://openalex.org/W2613485535","https://openalex.org/W2521559113"],"abstract_inverted_index":{"Abstract":[0],"This":[1],"study":[2],"was":[3,26,34,80],"designed":[4],"to":[5,176],"reconstruct":[6],"31\u2010band":[7],"spectral":[8,103,202,243],"reflectance":[9],"from":[10],"CIE":[11],"XYZ":[12,205],"values":[13,157],"using":[14],"an":[15,37,45,66,95],"extreme":[16],"learning":[17],"machine":[18],"(ELM),":[19],"and":[20,23,44,63,74,101,135,164,172,210],"its":[21],"within\u2010dataset":[22,215],"cross\u2010dataset":[24,227],"performance":[25,144],"evaluated.":[27],"The":[28,229],"Sino":[29,177],"dataset,":[30],"containing":[31],"10,770":[32],"samples,":[33],"divided":[35],"into":[36],"independent":[38,84],"20%":[39],"subset":[40,47],"for":[41,48,225,237],"hyperparameter":[42],"selection":[43],"80%":[46],"formal":[49],"evaluation.":[50],"By":[51],"means":[52],"of":[53,78,91,97,105,158],"a":[54,75,87,102,200],"full":[55],"grid":[56],"search":[57],"over":[58,191],"hidden\u2010layer":[59],"size,":[60],"activation":[61,73],"function":[62],"regularisation":[64,76],"coefficient,":[65],"ELM":[67,128],"with":[68,147,178,241],"350":[69],"hidden":[70],"neurons,":[71],"radbas":[72],"coefficient":[77],"0":[79],"selected.":[81],"On":[82],"the":[83,113,117,123,148,184,214,238],"evaluation":[85],"subset,":[86],"mean":[88,154],"\u0394E":[89,155],"00":[90,156],"0.082":[92],"\u00b1":[93,99,107,160,166],"0.002,":[94],"RMSE":[96],"0.005":[98],"0.000":[100],"angle":[104],"0.020":[106],"0.001":[108],"rad":[109],"were":[110,222],"achieved":[111,122],"by":[112],"optimised":[114],"ELM.":[115],"Among":[116],"seven":[118],"reconstruction":[119,125,141,188,216,244],"methods,":[120],"RBF":[121,134],"lowest":[124],"errors,":[126,217],"whereas":[127,170],"required":[129],"less":[130],"computational":[131],"time":[132],"than":[133,196],"BP":[136],"while":[137],"maintaining":[138],"relatively":[139],"low":[140,220],"errors.":[142,182,245],"Cross\u2010dataset":[143],"differed":[145],"markedly":[146],"training\u2010test":[149],"direction.":[150],"Sino\u2010trained":[151,185],"models":[152,174],"produced":[153],"7.936":[159],"0.361":[161],"on":[162,168],"Munsell":[163],"6.829":[165],"0.348":[167],"Coloro,":[169],"Munsell\u2010":[171],"Coloro\u2010trained":[173],"transferred":[175],"substantially":[179],"lower":[180],"colour\u2010difference":[181],"For":[183],"models,":[186],"large":[187],"errors":[189,221],"occurred":[190],"broad":[192],"wavelength":[193],"ranges":[194],"rather":[195],"being":[197],"concentrated":[198],"in":[199],"single":[201],"region.":[203],"Using":[204],"information":[206],"under":[207],"both":[208],"D65":[209],"illuminant":[211],"A":[212],"reduced":[213],"but":[218],"similarly":[219],"not":[223],"obtained":[224],"all":[226],"directions.":[228],"MI":[230],"ab":[231],"results":[232],"showed":[233],"poorer":[234],"cross\u2010illuminant":[235],"consistency":[236],"transfer":[239],"directions":[240],"larger":[242]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-04T00:00:00"}
