{"id":"https://openalex.org/W2291038393","doi":"https://doi.org/10.1109/sii.2015.7405017","title":"A object classification method using product of randomly selected elements","display_name":"A object classification method using product of randomly selected elements","publication_year":2015,"publication_date":"2015-12-01","ids":{"openalex":"https://openalex.org/W2291038393","doi":"https://doi.org/10.1109/sii.2015.7405017","mag":"2291038393"},"language":"en","primary_location":{"id":"doi:10.1109/sii.2015.7405017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii.2015.7405017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/SICE International Symposium on System Integration (SII)","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/A5000776598","display_name":"Naoki Morimoto","orcid":"https://orcid.org/0000-0002-9416-6217"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Naoki Morimoto","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I96636082"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103163418","display_name":"Kazuhiro Hotta","orcid":"https://orcid.org/0000-0002-5675-8713"},"institutions":[{"id":"https://openalex.org/I96636082","display_name":"Meijo University","ror":"https://ror.org/04h42fc75","country_code":"JP","type":"education","lineage":["https://openalex.org/I96636082"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhiro Hotta","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Meijo University, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I96636082"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5000776598"],"corresponding_institution_ids":["https://openalex.org/I96636082"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15123446,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"428","last_page":"432"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9977999925613403,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9973999857902527,"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/computer-science","display_name":"Computer science","score":0.7630998492240906},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7486655712127686},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.742688775062561},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7041664719581604},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6039904356002808},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.587558388710022},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.515070378780365},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5077289342880249},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4575539827346802},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4478949010372162},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34857088327407837},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2274763584136963},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05288887023925781}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7630998492240906},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7486655712127686},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.742688775062561},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7041664719581604},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6039904356002808},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.587558388710022},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.515070378780365},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5077289342880249},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4575539827346802},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4478949010372162},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34857088327407837},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2274763584136963},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05288887023925781},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii.2015.7405017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii.2015.7405017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1625255723","https://openalex.org/W2016053056","https://openalex.org/W2027922120","https://openalex.org/W2062118960","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2108598243","https://openalex.org/W2109255472","https://openalex.org/W2118585731","https://openalex.org/W2145287260","https://openalex.org/W2147414309","https://openalex.org/W2148603752","https://openalex.org/W2155893237","https://openalex.org/W2161381512","https://openalex.org/W2162915993","https://openalex.org/W2163605009","https://openalex.org/W2179352600","https://openalex.org/W2950094539","https://openalex.org/W6636494156","https://openalex.org/W6674914833","https://openalex.org/W6676297131","https://openalex.org/W6676338569","https://openalex.org/W6677656871","https://openalex.org/W6684191040","https://openalex.org/W7071374342"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W2530420969","https://openalex.org/W2565656575","https://openalex.org/W4390143830"],"abstract_inverted_index":{"In":[0,145],"recent":[1],"years,":[2],"we":[3,77,109,152],"treat":[4],"a":[5,88,105,122],"lot":[6],"of":[7,11,14,53,70,83,113,136,161],"images":[8,28],"easily":[9],"because":[10],"the":[12,51,57,64,68,74,81,93,126,130,146,149,159],"spread":[13],"smart":[15],"phones,":[16],"internet":[17],"and":[18,39,120,140],"digital":[19],"cameras,":[20],"etc.":[21],"To":[22,66],"search":[23],"or":[24,115],"put":[25],"tags":[26],"to":[27,79],"automatically,":[29],"an":[30],"object":[31,41],"classification":[32,42,106],"method":[33],"with":[34,125,132],"high":[35],"accuracy":[36,69,155],"is":[37,102,156],"required":[38],"many":[40,111],"methods":[43],"have":[44],"been":[45],"proposed.":[46],"Recent":[47],"some":[48],"papers":[49],"demonstrated":[50],"effectiveness":[52],"features":[54,71],"obtained":[55,72,91],"by":[56,73,92,158],"CNN":[58],"trained":[59,121],"from":[60,87],"1000":[61],"categories":[62],"in":[63],"ImageNet.":[65],"improve":[67],"pretrained":[75,94],"CNN,":[76],"propose":[78],"use":[80],"combination":[82,101,127,160],"elements":[84,119],"selected":[85,118,139,163],"randomly":[86,117,162],"feature":[89],"vector":[90],"CNN.":[95],"We":[96],"do":[97],"not":[98],"know":[99],"which":[100],"effective":[103],"for":[104,142],"task.":[107],"Thus,":[108],"compute":[110],"combinations":[112,131],"two":[114],"three":[116],"linear":[123],"SVM":[124,137],"feature.":[128],"Only":[129],"large":[133],"absolute":[134],"weight":[135],"are":[138],"used":[141],"final":[143],"classification.":[144],"experiments":[147],"using":[148],"CIFAR10":[150],"dataset,":[151],"confirmed":[153],"that":[154],"improved":[157],"elements.":[164]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}