{"id":"https://openalex.org/W2150871611","doi":"https://doi.org/10.1109/icme.2002.1035657","title":"Texture classification based on multiple Gauss mixture vector quantizers","display_name":"Texture classification based on multiple Gauss mixture vector quantizers","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2150871611","doi":"https://doi.org/10.1109/icme.2002.1035657","mag":"2150871611"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2002.1035657","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2002.1035657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Multimedia and Expo","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/A5054626081","display_name":"Kyungsuk Pyun","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kyungsuk Pyun","raw_affiliation_strings":["Dept. of Electrical Eng., Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Eng., Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049278507","display_name":"Chee Sun Won","orcid":"https://orcid.org/0000-0002-3400-0792"},"institutions":[{"id":"https://openalex.org/I205490536","display_name":"Dongguk University","ror":"https://ror.org/057q6n778","country_code":"KR","type":"education","lineage":["https://openalex.org/I205490536"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chee Sun Won","raw_affiliation_strings":["Dept. of Electronic Eng., Dongguk University, Seoul, Korea"],"affiliations":[{"raw_affiliation_string":"Dept. of Electronic Eng., Dongguk University, Seoul, Korea","institution_ids":["https://openalex.org/I205490536"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017417100","display_name":"Johan Lim","orcid":"https://orcid.org/0000-0003-3130-9820"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Johan Lim","raw_affiliation_strings":["Dept. of Statistics, Stanford University, Stanford, CA"],"affiliations":[{"raw_affiliation_string":"Dept. of Statistics, Stanford University, Stanford, CA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061042317","display_name":"Robert M. Gray","orcid":"https://orcid.org/0000-0002-6947-3637"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"R.M. Gray","raw_affiliation_strings":["Dept. of Electrical Eng., Stanford University, Stanford, CA, USA"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Eng., Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5054626081"],"corresponding_institution_ids":["https://openalex.org/I97018004"],"apc_list":null,"apc_paid":null,"fwci":1.8684,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.86934894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"501","last_page":"504"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9970999956130981,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9970999956130981,"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/T11309","display_name":"Music and Audio Processing","score":0.9904999732971191,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9900000095367432,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.9398671388626099},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6115996837615967},{"id":"https://openalex.org/keywords/vector-quantization","display_name":"Vector quantization","score":0.6043972969055176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5977922677993774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5820521712303162},{"id":"https://openalex.org/keywords/gauss","display_name":"Gauss","score":0.5497282147407532},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48793551325798035},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.4514172077178955},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4392206370830536},{"id":"https://openalex.org/keywords/linde\u2013buzo\u2013gray-algorithm","display_name":"Linde\u2013Buzo\u2013Gray algorithm","score":0.4162499010562897},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.41411101818084717},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3652119040489197},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.31732791662216187},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2851143479347229}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9398671388626099},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6115996837615967},{"id":"https://openalex.org/C199833920","wikidata":"https://www.wikidata.org/wiki/Q612536","display_name":"Vector quantization","level":2,"score":0.6043972969055176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5977922677993774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5820521712303162},{"id":"https://openalex.org/C161794534","wikidata":"https://www.wikidata.org/wiki/Q177493","display_name":"Gauss","level":2,"score":0.5497282147407532},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48793551325798035},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.4514172077178955},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4392206370830536},{"id":"https://openalex.org/C93372532","wikidata":"https://www.wikidata.org/wiki/Q6552455","display_name":"Linde\u2013Buzo\u2013Gray algorithm","level":3,"score":0.4162499010562897},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.41411101818084717},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3652119040489197},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.31732791662216187},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2851143479347229},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2002.1035657","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2002.1035657","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings. IEEE International Conference on Multimedia and Expo","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.5,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.47999998927116394,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W111804592","https://openalex.org/W1631110450","https://openalex.org/W1970728487","https://openalex.org/W1978238148","https://openalex.org/W2031586513","https://openalex.org/W2106420113","https://openalex.org/W2109138142","https://openalex.org/W2109336649","https://openalex.org/W2160013257","https://openalex.org/W2160732595","https://openalex.org/W2168977926"],"related_works":["https://openalex.org/W2017514583","https://openalex.org/W2352648934","https://openalex.org/W2391875658","https://openalex.org/W2100120615","https://openalex.org/W1929869830","https://openalex.org/W2017401491","https://openalex.org/W2387054321","https://openalex.org/W2158612577","https://openalex.org/W2148772884","https://openalex.org/W1681061148"],"abstract_inverted_index":{"We":[0,13,79],"propose":[1],"a":[2,15,31,39],"texture":[3,24,86,100],"classification":[4],"method":[5],"using":[6,25],"multiple":[7],"Gauss":[8,20],"mixture":[9,21],"vector":[10],"quantizers":[11],"(GMVQ).":[12],"designed":[14],"separate":[16],"model":[17],"codebook":[18],"or":[19],"for":[22,113],"each":[23],"the":[26,47,56,81,84,110],"generalized":[27],"Lloyd":[28],"algorithm":[29,82],"with":[30],"minimum":[32],"discrimination":[33],"information":[34],"(MDI)":[35],"distortion":[36],"based":[37],"on":[38],"training":[40],"data":[41],"set.":[42],"The":[43],"multi-codebook":[44],"structure":[45],"of":[46,55,61],"GMVQ":[48],"classifier":[49],"is":[50],"an":[51],"extension":[52],"to":[53,83,91,98],"images":[54],"isolated":[57],"utterance":[58],"speech":[59],"recognizer":[60],"J.E.":[62],"Shore":[63],"and":[64,73,88,106],"D.":[65],"Burton":[66],"(see":[67],"Proc.":[68],"Int.":[69],"Conf.":[70],"Acoust.,":[71],"Speech,":[72],"Sig.":[74],"Processing,":[75],"IEEE82Ch.1746-7,":[76],"p.907-10,":[77],"1982).":[78],"applied":[80],"Brodatz":[85],"database":[87],"showed":[89],"it":[90],"be":[92],"competitive":[93],"in":[94,96],"performance":[95],"comparison":[97],"other":[99],"classifiers.":[101],"Its":[102],"low":[103],"complexity":[104],"implementation":[105],"real-time":[107],"operation":[108],"make":[109],"approach":[111],"suitable":[112],"content-based":[114],"image":[115],"retrieval.":[116]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}