{"id":"https://openalex.org/W4394766130","doi":"https://doi.org/10.1007/s42001-024-00266-7","title":"Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition","display_name":"Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition","publication_year":2024,"publication_date":"2024-04-01","ids":{"openalex":"https://openalex.org/W4394766130","doi":"https://doi.org/10.1007/s42001-024-00266-7"},"language":"en","primary_location":{"id":"doi:10.1007/s42001-024-00266-7","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s42001-024-00266-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42001-024-00266-7.pdf","source":{"id":"https://openalex.org/S4210196583","display_name":"Journal of Computational Social Science","issn_l":"2432-2717","issn":["2432-2717","2432-2725"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Social Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s42001-024-00266-7.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5093339744","display_name":"Niels Griffioen","orcid":"https://orcid.org/0000-0002-7159-6708"},"institutions":[{"id":"https://openalex.org/I193700539","display_name":"Tilburg University","ror":"https://ror.org/04b8v1s79","country_code":"NL","type":"education","lineage":["https://openalex.org/I193700539"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Niels Griffioen","raw_affiliation_strings":["Department of Cognitive Science and Artificial Intelligence, Tilburg University, Waraandelan, 5037 AB, Tilburg, North-Brabant, Netherlands"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cognitive Science and Artificial Intelligence, Tilburg University, Waraandelan, 5037 AB, Tilburg, North-Brabant, Netherlands","institution_ids":["https://openalex.org/I193700539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064302239","display_name":"Nevena Rankovi\u0107","orcid":"https://orcid.org/0000-0002-9910-5886"},"institutions":[{"id":"https://openalex.org/I193700539","display_name":"Tilburg University","ror":"https://ror.org/04b8v1s79","country_code":"NL","type":"education","lineage":["https://openalex.org/I193700539"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Nevena Rankovic","raw_affiliation_strings":["Department of Cognitive Science and Artificial Intelligence, Tilburg University, Waraandelan, 5037 AB, Tilburg, North-Brabant, Netherlands"],"raw_orcid":"https://orcid.org/0000-0002-9910-5886","affiliations":[{"raw_affiliation_string":"Department of Cognitive Science and Artificial Intelligence, Tilburg University, Waraandelan, 5037 AB, Tilburg, North-Brabant, Netherlands","institution_ids":["https://openalex.org/I193700539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048583007","display_name":"Federico Zamberl\u00e1n","orcid":null},"institutions":[{"id":"https://openalex.org/I24354313","display_name":"Universidad de Buenos Aires","ror":"https://ror.org/0081fs513","country_code":"AR","type":"education","lineage":["https://openalex.org/I24354313"]}],"countries":["AR"],"is_corresponding":false,"raw_author_name":"Federico Zamberlan","raw_affiliation_strings":["Departamento de F\u00edsica, Universidad de Buenos Aires, Intendente G\u00fciraldes 2160, C1428EGA, Buenos Aires, Argentina"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departamento de F\u00edsica, Universidad de Buenos Aires, Intendente G\u00fciraldes 2160, C1428EGA, Buenos Aires, Argentina","institution_ids":["https://openalex.org/I24354313"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5095380981","display_name":"Monisha Punith","orcid":null},"institutions":[{"id":"https://openalex.org/I149213910","display_name":"University of Antwerp","ror":"https://ror.org/008x57b05","country_code":"BE","type":"education","lineage":["https://openalex.org/I149213910"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Monisha Punith","raw_affiliation_strings":["Department of economics, University of Antwerp, Prinsstraat 13, 2000, Antwerp, Flanders, Belgium"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of economics, University of Antwerp, Prinsstraat 13, 2000, Antwerp, Flanders, Belgium","institution_ids":["https://openalex.org/I149213910"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5064302239"],"corresponding_institution_ids":["https://openalex.org/I193700539"],"apc_list":{"value":2890,"currency":"USD","value_usd":2890},"apc_paid":{"value":2890,"currency":"USD","value_usd":2890},"fwci":0.729,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74460396,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"7","issue":"1","first_page":"1039","last_page":"1070"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9987999796867371,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/annotation","display_name":"Annotation","score":0.7236427664756775},{"id":"https://openalex.org/keywords/retraining","display_name":"Retraining","score":0.6904938817024231},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6395424008369446},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6251865029335022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5252337455749512},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4728696048259735},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.4104306399822235},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3283945918083191}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.7236427664756775},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.6904938817024231},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6395424008369446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6251865029335022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5252337455749512},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4728696048259735},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4104306399822235},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3283945918083191},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C155202549","wikidata":"https://www.wikidata.org/wiki/Q178803","display_name":"International trade","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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":6,"locations":[{"id":"doi:10.1007/s42001-024-00266-7","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s42001-024-00266-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42001-024-00266-7.pdf","source":{"id":"https://openalex.org/S4210196583","display_name":"Journal of Computational Social Science","issn_l":"2432-2717","issn":["2432-2717","2432-2725"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Social Science","raw_type":"journal-article"},{"id":"pmh:oai:tilburguniversity.edu:openaire/544d20d5-2b8e-4483-b9dd-b2be4d161c17","is_oa":true,"landing_page_url":"https://research.tilburguniversity.edu/en/publications/544d20d5-2b8e-4483-b9dd-b2be4d161c17","pdf_url":null,"source":{"id":"https://openalex.org/S4306401490","display_name":"Research portal (Tilburg University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193700539","host_organization_name":"Tilburg University","host_organization_lineage":["https://openalex.org/I193700539"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Griffioen, N, Rankovi\u0107, N, Zamberlan, F & Punith, M 2024, 'Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition', Journal of Computational Social Science, vol. 7, pp. 1039-1070. https://doi.org/10.1007/s42001-024-00266-7","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:20.500.12942/744482","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/20.500.12942/744482","pdf_url":"https://lirias.kuleuven.be/retrieve/e0427580-1c15-4aff-a6df-bee2b51c592e","source":{"id":"https://openalex.org/S7407055369","display_name":"Lirias","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Computational Social Science, vol. 7 (1), (1039-1070)","raw_type":"info:eu-repo/semantics/article"},{"id":"pmh:c:irua:205436","is_oa":false,"landing_page_url":"https://hdl.handle.net/10067/2054360151162165141","pdf_url":null,"source":{"id":"https://openalex.org/S4306401849","display_name":"Institutional Repository University of Antwerp (University of Antwerp)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149213910","host_organization_name":"University of Antwerp","host_organization_lineage":["https://openalex.org/I149213910"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":""},{"id":"pmh:oai:RePEc:spr:jcsosc:v:7:y:2024:i:1:d:10.1007_s42001-024-00266-7","is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s42001-024-00266-7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:tilburguniversity.edu:publications/544d20d5-2b8e-4483-b9dd-b2be4d161c17","is_oa":true,"landing_page_url":"https://www.scopus.com/pages/publications/85190087582","pdf_url":null,"source":{"id":"https://openalex.org/S4306401490","display_name":"Research portal (Tilburg University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193700539","host_organization_name":"Tilburg University","host_organization_lineage":["https://openalex.org/I193700539"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Griffioen, N, Rankovi\u0107, N, Zamberlan, F & Punith, M 2024, 'Efficient annotation reduction with active learning for computer vision-based Retail Product Recognition', Journal of Computational Social Science, vol. 7, pp. 1039-1070. https://doi.org/10.1007/s42001-024-00266-7","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s42001-024-00266-7","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1007/s42001-024-00266-7","pdf_url":"https://link.springer.com/content/pdf/10.1007/s42001-024-00266-7.pdf","source":{"id":"https://openalex.org/S4210196583","display_name":"Journal of Computational Social Science","issn_l":"2432-2717","issn":["2432-2717","2432-2725"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computational Social Science","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4394766130.pdf"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2037227137","https://openalex.org/W2088049833","https://openalex.org/W2112796928","https://openalex.org/W2117763124","https://openalex.org/W2147880316","https://openalex.org/W2171671120","https://openalex.org/W2194775991","https://openalex.org/W2340897893","https://openalex.org/W2395611524","https://openalex.org/W2471138382","https://openalex.org/W2557889580","https://openalex.org/W2740558313","https://openalex.org/W2884367402","https://openalex.org/W2921056832","https://openalex.org/W2951061410","https://openalex.org/W2963150697","https://openalex.org/W2963539956","https://openalex.org/W2977942577","https://openalex.org/W2983005688","https://openalex.org/W3105335547","https://openalex.org/W3126755025","https://openalex.org/W3179550234","https://openalex.org/W3187289500","https://openalex.org/W3205626500","https://openalex.org/W4205743601","https://openalex.org/W4212774754","https://openalex.org/W4220755889","https://openalex.org/W4290065491","https://openalex.org/W4292794843","https://openalex.org/W4298132949","https://openalex.org/W4304687536","https://openalex.org/W6799650303"],"related_works":["https://openalex.org/W2081982437","https://openalex.org/W4394857231","https://openalex.org/W2027050655","https://openalex.org/W3028244590","https://openalex.org/W4254349500","https://openalex.org/W2014369232","https://openalex.org/W3122042562","https://openalex.org/W2050078012","https://openalex.org/W2060761133","https://openalex.org/W4206195464"],"abstract_inverted_index":{"Abstract":[0],"The":[1,66,96],"retail":[2,64,192,209],"industry":[3],"encounters":[4],"huge":[5],"obstacles":[6],"with":[7,17,92],"computer":[8],"vision":[9],"(CV)":[10],"technology":[11],"due":[12],"to":[13,51,58,74,159],"frequent":[14],"model":[15,36],"retraining":[16],"changing":[18],"products":[19],"and":[20,86,129,146,180,201],"time-consuming,":[21],"costly":[22],"data":[23,111,122,175],"annotation.":[24],"Previous":[25],"research":[26],"in":[27,62],"this":[28,48],"field":[29],"has":[30],"been":[31],"primarily":[32],"focused":[33],"on":[34,189],"optimizing":[35],"performance":[37],"rather":[38],"than":[39],"minimizing":[40],"annotation":[41,60,133],"effort.":[42],"Therefore,":[43],"the":[44,63,82,110,115,126,149,154,160,167,174,184,196,208],"main":[45],"idea":[46],"of":[47,109,114,148,166,198],"paper":[49],"is":[50,72],"evaluate":[52,75],"active":[53,77,186],"learning":[54,78,187],"as":[55,81],"a":[56,170],"method":[57,156],"minimize":[59],"effort":[61],"industry.":[65,210],"MVTEC":[67],"Densely":[68],"Segmented":[69],"Supermarket":[70],"dataset":[71,193],"used":[73],"various":[76],"methods":[79,131,168,188],"such":[80],"Least":[83,127],"Confident,":[84],"Entropy":[85,155],"Cost-Effective":[87],"Active":[88],"Learning":[89],"(CEAL)":[90],"along":[91],"Mask":[93],"R-CNN":[94],"model.":[95],"results":[97],"demonstrate":[98],"that":[99],"annotating":[100],"only":[101],"20.83":[102],"$$-$$":[103,137],"<mml:math":[104,138],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[105,139],"<mml:mo>-</mml:mo>":[106,140],"</mml:math>":[107,141],"24.34%":[108],"achieves":[112],"95%":[113,145],"full":[116,150],"dataset\u2019s":[117,151],"performance.":[118,152],"When":[119],"training,":[120],"out-of-sample":[121,181],"share":[123],"similar":[124],"characteristics,":[125],"Confident":[128],"CEAL":[130],"reduce":[132],"requirements":[134],"by":[135],"7.7":[136],"15.7%":[142],"while":[143],"maintaining":[144],"97%":[147],"However,":[153],"under-performs":[157],"compared":[158],"random":[161],"selection":[162],"baseline.":[163],"Ultimately,":[164],"none":[165],"show":[169],"clear":[171],"advantage":[172],"when":[173],"characteristics":[176],"differ":[177],"between":[178],"training":[179],"data.":[182],"Finally,":[183],"proposed":[185],"an":[190],"industry-specific":[191],"remarkably":[194],"propels":[195],"development":[197],"highly":[199],"efficient":[200],"cost-effective":[202],"CV":[203],"solutions":[204],"meticulously":[205],"tailored":[206],"for":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-23T08:03:31.855105","created_date":"2025-10-10T00:00:00"}
