{"id":"https://openalex.org/W3196115329","doi":"https://doi.org/10.23919/mva51890.2021.9511391","title":"Cut and paste curriculum learning with hard negative mining for point-of-sale systems","display_name":"Cut and paste curriculum learning with hard negative mining for point-of-sale systems","publication_year":2021,"publication_date":"2021-07-25","ids":{"openalex":"https://openalex.org/W3196115329","doi":"https://doi.org/10.23919/mva51890.2021.9511391","mag":"3196115329"},"language":"en","primary_location":{"id":"doi:10.23919/mva51890.2021.9511391","is_oa":false,"landing_page_url":"https://doi.org/10.23919/mva51890.2021.9511391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Machine Vision and Applications (MVA)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035701426","display_name":"Jaechul Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114283","display_name":"Kyocera (Japan)","ror":"https://ror.org/025y1g718","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210114283"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jaechul Kim","raw_affiliation_strings":["Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan","institution_ids":["https://openalex.org/I4210114283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100516929","display_name":"Xiaoyan Dai","orcid":"https://orcid.org/0000-0003-2776-3924"},"institutions":[{"id":"https://openalex.org/I4210114283","display_name":"Kyocera (Japan)","ror":"https://ror.org/025y1g718","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210114283"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Xiaoyan Dai","raw_affiliation_strings":["Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan","institution_ids":["https://openalex.org/I4210114283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006000263","display_name":"Yisan Hsieh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114283","display_name":"Kyocera (Japan)","ror":"https://ror.org/025y1g718","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210114283"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yisan Hsieh","raw_affiliation_strings":["Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan","institution_ids":["https://openalex.org/I4210114283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061183126","display_name":"Hiroki Tanimoto","orcid":"https://orcid.org/0000-0002-4121-6807"},"institutions":[{"id":"https://openalex.org/I4210114283","display_name":"Kyocera (Japan)","ror":"https://ror.org/025y1g718","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210114283"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Tanimoto","raw_affiliation_strings":["Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Advanced Technology Research Institue, Minatomirai Research Center Kyocera Corporation, Yokohama, Japan","institution_ids":["https://openalex.org/I4210114283"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050137607","display_name":"Hironobu Fujivoshi","orcid":null},"institutions":[{"id":"https://openalex.org/I184937672","display_name":"Chubu University","ror":"https://ror.org/02sps0775","country_code":"JP","type":"education","lineage":["https://openalex.org/I184937672"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hironobu Fujivoshi","raw_affiliation_strings":["Chubu University, Aichi, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chubu University, Aichi, Japan","institution_ids":["https://openalex.org/I184937672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.394,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.49960322,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9991000294685364,"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":0.9991000294685364,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9930999875068665,"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/T13270","display_name":"QR Code Applications and Technologies","score":0.9789999723434448,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.7134724855422974},{"id":"https://openalex.org/keywords/curriculum","display_name":"Curriculum","score":0.6852603554725647},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6656464338302612},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6218560338020325},{"id":"https://openalex.org/keywords/realization","display_name":"Realization (probability)","score":0.577958345413208},{"id":"https://openalex.org/keywords/automation","display_name":"Automation","score":0.5135243535041809},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5132255554199219},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.46515899896621704},{"id":"https://openalex.org/keywords/test","display_name":"Test (biology)","score":0.4627665579319},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1781904101371765},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10022380948066711}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7134724855422974},{"id":"https://openalex.org/C47177190","wikidata":"https://www.wikidata.org/wiki/Q207137","display_name":"Curriculum","level":2,"score":0.6852603554725647},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6656464338302612},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6218560338020325},{"id":"https://openalex.org/C2781089630","wikidata":"https://www.wikidata.org/wiki/Q21856745","display_name":"Realization (probability)","level":2,"score":0.577958345413208},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.5135243535041809},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5132255554199219},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.46515899896621704},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.4627665579319},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1781904101371765},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10022380948066711},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/mva51890.2021.9511391","is_oa":false,"landing_page_url":"https://doi.org/10.23919/mva51890.2021.9511391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 17th International Conference on Machine Vision and Applications (MVA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2031489346","https://openalex.org/W2037227137","https://openalex.org/W2117539524","https://openalex.org/W2513267962","https://openalex.org/W2560474170","https://openalex.org/W2744438518","https://openalex.org/W2746314669","https://openalex.org/W2765407302","https://openalex.org/W2790630087","https://openalex.org/W2791492630","https://openalex.org/W2887368306","https://openalex.org/W2963271314","https://openalex.org/W2963458902","https://openalex.org/W2963516811","https://openalex.org/W2965187458","https://openalex.org/W2992308087","https://openalex.org/W3106250896","https://openalex.org/W6743428213"],"related_works":["https://openalex.org/W2022544890","https://openalex.org/W2394097730","https://openalex.org/W2475378634","https://openalex.org/W4312353617","https://openalex.org/W2113405914","https://openalex.org/W2260963831","https://openalex.org/W4235249401","https://openalex.org/W2331305369","https://openalex.org/W2043523297","https://openalex.org/W2015200445"],"abstract_inverted_index":{"Although":[0],"point-of-sale":[1],"(POS)":[2],"systems":[3,21],"generally":[4],"use":[5,22],"barcodes,":[6],"progress":[7,84],"in":[8,10,76],"automation":[9],"recent":[11],"years":[12],"has":[13,78],"come":[14],"to":[15,26,34,38,65,99,130,150,152],"require":[16],"real-time":[17,156],"performance.":[18],"Since":[19],"these":[20],"machine":[23,71],"learning":[24,62,75,83,93,102,109,137],"models":[25,32],"detect":[27],"products":[28],"from":[29,53],"images,":[30],"the":[31,40,79,101,125,135,153],"need":[33],"be":[35],"retrained":[36],"frequently":[37],"support":[39],"continual":[41],"release":[42],"of":[43,57,69,155],"new":[44,91],"products.":[45],"Thus,":[46],"methods":[47],"for":[48],"efficiently":[49],"training":[50],"a":[51,54,90,107],"model":[52],"limited":[55],"amount":[56],"data":[58],"are":[59],"needed.":[60],"Curriculum":[61],"was":[63],"developed":[64,89],"achieve":[66,131],"this":[67],"kind":[68],"efficient":[70],"learning.":[72],"However,":[73],"curriculum":[74,92],"general":[77],"problem":[80],"that":[81],"early":[82],"is":[85,128],"slow.":[86],"Therefore,":[87],"we":[88],"method":[94,105,119,127,149],"using":[95],"hard":[96],"negative":[97],"mining":[98],"boost":[100],"progress.":[103],"This":[104],"provides":[106],"remarkable":[108],"effect":[110],"through":[111],"simple":[112],"cut":[113,142],"and":[114,124,143,157],"paste.":[115],"We":[116,146],"test":[117,122],"our":[118,148],"on":[120],"various":[121],"data,":[123],"proposed":[126],"found":[129],"better":[132],"performance":[133],"at":[134],"same":[136],"epoch":[138],"compared":[139],"with":[140],"conventional":[141],"paste":[144],"methods.":[145],"expect":[147],"contribute":[151],"realization":[154],"easy-to-operate":[158],"POS":[159],"systems.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}