{"id":"https://openalex.org/W1989993745","doi":"https://doi.org/10.1109/ijcnn.1990.137762","title":"Reconstruction of Munsell color space by a five-layered neural network","display_name":"Reconstruction of Munsell color space by a five-layered neural network","publication_year":1990,"publication_date":"1990-01-01","ids":{"openalex":"https://openalex.org/W1989993745","doi":"https://doi.org/10.1109/ijcnn.1990.137762","mag":"1989993745"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.1990.137762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.1990.137762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1990 IJCNN International Joint Conference on Neural Networks","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/A5109216703","display_name":"S. Usui","orcid":null},"institutions":[{"id":"https://openalex.org/I136259955","display_name":"Toyohashi University of Technology","ror":"https://ror.org/04ezg6d83","country_code":"JP","type":"education","lineage":["https://openalex.org/I136259955"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"S. Usui","raw_affiliation_strings":["Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi, Japan","institution_ids":["https://openalex.org/I136259955"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050167244","display_name":"Shigeki Nakauchi","orcid":"https://orcid.org/0000-0002-4954-6915"},"institutions":[{"id":"https://openalex.org/I136259955","display_name":"Toyohashi University of Technology","ror":"https://ror.org/04ezg6d83","country_code":"JP","type":"education","lineage":["https://openalex.org/I136259955"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"S. Nakauchi","raw_affiliation_strings":["Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi, Japan","institution_ids":["https://openalex.org/I136259955"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054188506","display_name":"M. Nakano","orcid":null},"institutions":[{"id":"https://openalex.org/I136259955","display_name":"Toyohashi University of Technology","ror":"https://ror.org/04ezg6d83","country_code":"JP","type":"education","lineage":["https://openalex.org/I136259955"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"M. Nakano","raw_affiliation_strings":["Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Information and Computer Sciences, Toyohashi University of Technology, Toyohashi, Japan","institution_ids":["https://openalex.org/I136259955"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5109216703"],"corresponding_institution_ids":["https://openalex.org/I136259955"],"apc_list":null,"apc_paid":null,"fwci":1.1456,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.73949045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"515","last_page":"520 vol.2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9979000091552734,"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":0.9979000091552734,"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/T10427","display_name":"Visual perception and processing mechanisms","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9415000081062317,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/color-space","display_name":"Color space","score":0.7708561420440674},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7208060622215271},{"id":"https://openalex.org/keywords/icc-profile","display_name":"ICC profile","score":0.6462284922599792},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6375746130943298},{"id":"https://openalex.org/keywords/backpropagation","display_name":"Backpropagation","score":0.5928357839584351},{"id":"https://openalex.org/keywords/hue","display_name":"Hue","score":0.5923352241516113},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5705640912055969},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5544033050537109},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5302959084510803},{"id":"https://openalex.org/keywords/color-difference","display_name":"Color difference","score":0.44851118326187134},{"id":"https://openalex.org/keywords/high-color","display_name":"High color","score":0.44450920820236206},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.365821897983551},{"id":"https://openalex.org/keywords/color-model","display_name":"Color model","score":0.3539697527885437},{"id":"https://openalex.org/keywords/color-image","display_name":"Color image","score":0.3266686201095581},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.17374813556671143},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.17184039950370789}],"concepts":[{"id":"https://openalex.org/C2961294","wikidata":"https://www.wikidata.org/wiki/Q166863","display_name":"Color space","level":3,"score":0.7708561420440674},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7208060622215271},{"id":"https://openalex.org/C95143428","wikidata":"https://www.wikidata.org/wiki/Q375296","display_name":"ICC profile","level":5,"score":0.6462284922599792},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6375746130943298},{"id":"https://openalex.org/C155032097","wikidata":"https://www.wikidata.org/wiki/Q798503","display_name":"Backpropagation","level":3,"score":0.5928357839584351},{"id":"https://openalex.org/C126537357","wikidata":"https://www.wikidata.org/wiki/Q372948","display_name":"Hue","level":2,"score":0.5923352241516113},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5705640912055969},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5544033050537109},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5302959084510803},{"id":"https://openalex.org/C186991048","wikidata":"https://www.wikidata.org/wiki/Q1184883","display_name":"Color difference","level":3,"score":0.44851118326187134},{"id":"https://openalex.org/C131910990","wikidata":"https://www.wikidata.org/wiki/Q1202284","display_name":"High color","level":5,"score":0.44450920820236206},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.365821897983551},{"id":"https://openalex.org/C36262787","wikidata":"https://www.wikidata.org/wiki/Q2294018","display_name":"Color model","level":4,"score":0.3539697527885437},{"id":"https://openalex.org/C142616399","wikidata":"https://www.wikidata.org/wiki/Q5148604","display_name":"Color image","level":4,"score":0.3266686201095581},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.17374813556671143},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.17184039950370789},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.1990.137762","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.1990.137762","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"1990 IJCNN International Joint Conference on Neural Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1971179077","https://openalex.org/W1971735090","https://openalex.org/W1984699170","https://openalex.org/W1987721959","https://openalex.org/W2000076583","https://openalex.org/W2014403078","https://openalex.org/W2017257315","https://openalex.org/W2038002084","https://openalex.org/W2047881670","https://openalex.org/W2151850352","https://openalex.org/W2559845173","https://openalex.org/W3034434323","https://openalex.org/W6730283569","https://openalex.org/W6779371258"],"related_works":["https://openalex.org/W2288745280","https://openalex.org/W4378445973","https://openalex.org/W1992936402","https://openalex.org/W4255532429","https://openalex.org/W2377180853","https://openalex.org/W2070857196","https://openalex.org/W2145332469","https://openalex.org/W2113523510","https://openalex.org/W2385373070","https://openalex.org/W2390727152"],"abstract_inverted_index":{"A":[0],"wine-glass-type":[1],"five-layered":[2,138],"neural":[3,139],"network":[4,33],"(81-10-3-10-81)":[5],"has":[6,12],"been":[7,13],"constructed,":[8],"and":[9,41,111,131],"identity":[10,60],"mapping":[11,61],"realized":[14],"on":[15],"the":[16,65,69,74,81,109,112,117,122,129,150,156],"set":[17],"of":[18,23,51,68,84,121,128],"surface":[19],"spectral":[20,45],"reflectance":[21,46],"data":[22,47],"Munsell":[24,123],"color":[25,52,85,103,124,151],"chips":[26],"by":[27,88],"a":[28,91],"backpropagation":[29],"learning":[30,62],"algorithm.":[31],"The":[32,133],"is":[34,141],"divided":[35],"into":[36],"two":[37,114],"parts:":[38],"encoder":[39],"(81-10-3)":[40],"decoder":[42],"(3-10-81).":[43],"Surface":[44],"as":[48],"physical":[49],"attributes":[50],"are":[53],"transformed":[54],"nonlinearly":[55],"in":[56,73,155],"each":[57,97],"part.":[58],"After":[59],"was":[63,77,94],"completed,":[64],"response":[66],"pattern":[67],"three":[70],"hidden":[71,98],"units":[72,115],"middle":[75],"layer":[76],"analyzed":[78],"to":[79,101,143],"obtain":[80],"internal":[82],"representation":[83],"information":[86,152],"acquired":[87],"self-learning.":[89],"As":[90],"result,":[92],"it":[93],"found":[95],"that":[96,105],"unit":[99],"responds":[100],"psychological":[102],"attributes,":[104],"is,":[106],"one":[107],"for":[108,116,148],"value":[110,119],"other":[113],"constant":[118],"plane":[120],"system":[125,158],"which":[126],"consists":[127],"hue":[130],"chroma.":[132],"nonlinear":[134],"analysis":[135],"method":[136,147],"using":[137],"networks":[140],"shown":[142],"be":[144],"an":[145],"efficient":[146],"elucidating":[149],"coding":[153],"mechanisms":[154],"visual":[157]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
