{"id":"https://openalex.org/W4399375117","doi":"https://doi.org/10.1109/icit58233.2024.10540748","title":"Texture Image Classification Using LLGMN and HLAC Features","display_name":"Texture Image Classification Using LLGMN and HLAC Features","publication_year":2024,"publication_date":"2024-03-25","ids":{"openalex":"https://openalex.org/W4399375117","doi":"https://doi.org/10.1109/icit58233.2024.10540748"},"language":"en","primary_location":{"id":"doi:10.1109/icit58233.2024.10540748","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icit58233.2024.10540748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Technology (ICIT)","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/A5089342152","display_name":"Taiga Eguchi","orcid":"https://orcid.org/0000-0002-3248-6418"},"institutions":[{"id":"https://openalex.org/I177136067","display_name":"Saga University","ror":"https://ror.org/04f4wg107","country_code":"JP","type":"education","lineage":["https://openalex.org/I177136067"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taiga Eguchi","raw_affiliation_strings":["Saga University,Faculty of Science and Engineering,Saga,Japan","Faculty of Science and Engineering, Saga University, Saga, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saga University,Faculty of Science and Engineering,Saga,Japan","institution_ids":["https://openalex.org/I177136067"]},{"raw_affiliation_string":"Faculty of Science and Engineering, Saga University, Saga, Japan","institution_ids":["https://openalex.org/I177136067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013982415","display_name":"Osamu Fukuda","orcid":null},"institutions":[{"id":"https://openalex.org/I177136067","display_name":"Saga University","ror":"https://ror.org/04f4wg107","country_code":"JP","type":"education","lineage":["https://openalex.org/I177136067"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Osamu Fukuda","raw_affiliation_strings":["Saga University,Faculty of Science and Engineering,Saga,Japan","Faculty of Science and Engineering, Saga University, Saga, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saga University,Faculty of Science and Engineering,Saga,Japan","institution_ids":["https://openalex.org/I177136067"]},{"raw_affiliation_string":"Faculty of Science and Engineering, Saga University, Saga, Japan","institution_ids":["https://openalex.org/I177136067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040208746","display_name":"Wen Liang Yeoh","orcid":"https://orcid.org/0000-0003-1272-9010"},"institutions":[{"id":"https://openalex.org/I177136067","display_name":"Saga University","ror":"https://ror.org/04f4wg107","country_code":"JP","type":"education","lineage":["https://openalex.org/I177136067"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Wen Liang Yeoh","raw_affiliation_strings":["Saga University,Faculty of Science and Engineering,Saga,Japan","Faculty of Science and Engineering, Saga University, Saga, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saga University,Faculty of Science and Engineering,Saga,Japan","institution_ids":["https://openalex.org/I177136067"]},{"raw_affiliation_string":"Faculty of Science and Engineering, Saga University, Saga, Japan","institution_ids":["https://openalex.org/I177136067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112676396","display_name":"Hiroshi Okumura","orcid":null},"institutions":[{"id":"https://openalex.org/I177136067","display_name":"Saga University","ror":"https://ror.org/04f4wg107","country_code":"JP","type":"education","lineage":["https://openalex.org/I177136067"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroshi Okumura","raw_affiliation_strings":["Saga University,Faculty of Science and Engineering,Saga,Japan","Faculty of Science and Engineering, Saga University, Saga, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saga University,Faculty of Science and Engineering,Saga,Japan","institution_ids":["https://openalex.org/I177136067"]},{"raw_affiliation_string":"Faculty of Science and Engineering, Saga University, Saga, Japan","institution_ids":["https://openalex.org/I177136067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038267059","display_name":"Nobuhiko Yamaguchi","orcid":"https://orcid.org/0000-0001-6172-4238"},"institutions":[{"id":"https://openalex.org/I177136067","display_name":"Saga University","ror":"https://ror.org/04f4wg107","country_code":"JP","type":"education","lineage":["https://openalex.org/I177136067"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nobuhiko Yamaguchi","raw_affiliation_strings":["Saga University,Faculty of Science and Engineering,Saga,Japan","Faculty of Science and Engineering, Saga University, Saga, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saga University,Faculty of Science and Engineering,Saga,Japan","institution_ids":["https://openalex.org/I177136067"]},{"raw_affiliation_string":"Faculty of Science and Engineering, Saga University, Saga, Japan","institution_ids":["https://openalex.org/I177136067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09710923,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"34","issue":null,"first_page":"1","last_page":"6"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9902999997138977,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9883000254631042,"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/principal-component-analysis","display_name":"Principal component analysis","score":0.7326000928878784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7168254852294922},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6897727251052856},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6443726420402527},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6009483337402344},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.5843520164489746},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.5038401484489441},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.47642025351524353},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4745940864086151},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.46164435148239136},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3928639888763428},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3834809958934784},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.2802274525165558}],"concepts":[{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7326000928878784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7168254852294922},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6897727251052856},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6443726420402527},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6009483337402344},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5843520164489746},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.5038401484489441},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.47642025351524353},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4745940864086151},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.46164435148239136},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3928639888763428},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3834809958934784},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2802274525165558},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icit58233.2024.10540748","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/icit58233.2024.10540748","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Industrial Technology (ICIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5899999737739563,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1588043677","https://openalex.org/W2004313226","https://openalex.org/W2026445526","https://openalex.org/W2064353911","https://openalex.org/W2087475904","https://openalex.org/W2108598243","https://openalex.org/W2112299124","https://openalex.org/W2122621634","https://openalex.org/W2133201420","https://openalex.org/W2294798173","https://openalex.org/W2305887293","https://openalex.org/W2309754896","https://openalex.org/W2516194221","https://openalex.org/W2571792182","https://openalex.org/W2622826443","https://openalex.org/W2760957381","https://openalex.org/W2785867322","https://openalex.org/W2797996008","https://openalex.org/W2907648650","https://openalex.org/W2963037989","https://openalex.org/W4206696821","https://openalex.org/W4225164818","https://openalex.org/W4238856144","https://openalex.org/W4321780078","https://openalex.org/W6604815279"],"related_works":["https://openalex.org/W1975632186","https://openalex.org/W2200355885","https://openalex.org/W2044270176","https://openalex.org/W2374828682","https://openalex.org/W2153116791","https://openalex.org/W2388733570","https://openalex.org/W4230530180","https://openalex.org/W1980033651","https://openalex.org/W2134401318","https://openalex.org/W1555506570"],"abstract_inverted_index":{"In":[0,33],"the":[1,10,18,66,77],"manufacturing":[2,122],"sector,":[3],"there":[4],"is":[5,31,84],"a":[6,54,95,102,110],"continuous":[7],"demand":[8],"for":[9],"high-quality,":[11],"low-volume":[12],"production":[13],"of":[14,20,26,70,91,98,105],"diverse":[15],"products":[16,27],"from":[17,65],"perspective":[19],"diversifying":[21],"customer":[22],"needs.":[23],"The":[24],"classification":[25],"with":[28,94],"complex":[29],"textures":[30],"challenging.":[32],"this":[34],"study,":[35],"we":[36,80,117],"classify":[37,88],"artificially":[38],"generated":[39],"texture":[40,92],"images":[41,93],"using":[42],"Log-Linearized":[43],"Gaussian":[44],"Mixture":[45],"Networks":[46],"(LLGMN),":[47],"which":[48],"are":[49],"neural":[50],"networks":[51],"based":[52],"on":[53,109,114],"probabilistic":[55],"statistical":[56],"model.":[57],"This":[58],"was":[59],"achieved":[60],"by":[61],"inputting":[62],"features":[63,74],"obtained":[64],"principal":[67],"component":[68],"analysis":[69],"Higher-order":[71],"Local":[72],"Auto-Correlation":[73],"(HLAC).":[75],"Using":[76],"proposed":[78],"method,":[79],"demonstrate":[81],"that":[82,124],"it":[83],"possible":[85],"to":[86],"quickly":[87],"six":[89],"classes":[90],"high":[96],"accuracy":[97],"98":[99],"%":[100],"and":[101],"training":[103],"time":[104],"approximately":[106],"60":[107],"s":[108],"standard":[111],"PC.":[112],"Based":[113],"these":[115],"results,":[116],"anticipate":[118],"potential":[119],"applications":[120],"in":[121],"sectors":[123],"require":[125],"fast":[126],"texture-image":[127],"classification.":[128]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}