{"id":"https://openalex.org/W107465220","doi":"https://doi.org/10.13182/fst12-a14626","title":"Active Learning Using Conformal Predictors: Application to Image Classification","display_name":"Active Learning Using Conformal Predictors: Application to Image Classification","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W107465220","doi":"https://doi.org/10.13182/fst12-a14626","mag":"107465220"},"language":"en","primary_location":{"id":"doi:10.13182/fst12-a14626","doi":"https://doi.org/10.13182/fst12-a14626","is_oa":false,"landing_page_url":"https://doi.org/10.13182/fst12-a14626","pdf_url":null,"source":{"id":"https://openalex.org/S104092111","display_name":"Fusion Science & Technology","issn_l":"1536-1055","issn":["1536-1055","1943-7641"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fusion Science and Technology","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5027531406","display_name":"L\u00e1zaro Em\u00edlio Makili","orcid":"https://orcid.org/0000-0002-7371-1407","observed_orcids":["https://orcid.org/0000-0002-7371-1407"]},"institutions":[{"id":"https://openalex.org/I4210120595","display_name":"Universidade Katyavala Bwila","ror":"https://ror.org/01vstb938","country_code":"AO","type":"education","lineage":["https://openalex.org/I4210120595"]}],"countries":["AO"],"is_corresponding":false,"raw_author_name":"L\u00e1zaro Em\u00edlio Makili","raw_affiliation_strings":["Instituto Superior Polit\u00e9cnico da Universidade Katyavala Bwila, Benguela, Angola"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Superior Polit\u00e9cnico da Universidade Katyavala Bwila, Benguela, Angola","institution_ids":["https://openalex.org/I4210120595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100907631","display_name":"Jes\u00fas Antonio Vega S\u00e1nchez","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210165411","display_name":"Centro de Investigaciones Energ\u00e9ticas, Medioambientales y Tecnol\u00f3gicas","ror":"https://ror.org/05xx77y52","country_code":"ES","type":"facility","lineage":["https://openalex.org/I4210165411"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jes\u00fas A. Vega S\u00e1nchez","raw_affiliation_strings":["Asociaci\u00f3n EURATOM/CIEMAT para Fusi\u00f3n, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Asociaci\u00f3n EURATOM/CIEMAT para Fusi\u00f3n, Madrid, Spain","institution_ids":["https://openalex.org/I4210165411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071036387","display_name":"S. Dormido-Canto","orcid":"https://orcid.org/0000-0001-7652-5338","observed_orcids":["https://orcid.org/0000-0001-7652-5338"]},"institutions":[{"id":"https://openalex.org/I178450904","display_name":"Universidad Nacional de Educaci\u00f3n a Distancia","ror":"https://ror.org/02msb5n36","country_code":"ES","type":"education","lineage":["https://openalex.org/I178450904"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Sebasti\u00e1n Dormido-Canto","raw_affiliation_strings":["UNED, Dpto. de Inform\u00e1tica y Autom\u00e1tica, Madrid, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"UNED, Dpto. de Inform\u00e1tica y Autom\u00e1tica, Madrid, Spain","institution_ids":["https://openalex.org/I178450904"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8706,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.75407336,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":97},"biblio":{"volume":"62","issue":"2","first_page":"347","last_page":"355"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","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"}},"topics":[{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","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"}},{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.0007999999797903001,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.0003000000142492354,"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/active-learning-machine-learning","display_name":"active learning (machine learning)","score":1.0},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.9580000042915344},{"id":"https://openalex.org/keywords/training-sample-selection","display_name":"training data selection","score":0.828000009059906},{"id":"https://openalex.org/keywords/haar-wavelet-transform","display_name":"Haar wavelet transform","score":0.8029999732971191},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"dimensionality reduction","score":0.7319999933242798},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8489999771118164},{"id":"https://openalex.org/keywords/overfitting","display_name":"overfitting","score":0.7440000176429749},{"id":"https://openalex.org/keywords/generalization","display_name":"generalization","score":0.7570000290870667},{"id":"https://openalex.org/keywords/reliability-metrics","display_name":"reliability measures","score":0.7229999899864197}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8015933036804199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7125705480575562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6796876192092896},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6156501173973083},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5872747898101807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5832511186599731},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5167555212974548},{"id":"https://openalex.org/C98214594","wikidata":"https://www.wikidata.org/wiki/Q850275","display_name":"Conformal map","level":2,"score":0.5058012008666992},{"id":"https://openalex.org/C2780423554","wikidata":"https://www.wikidata.org/wiki/Q766198","display_name":"Haar wavelet","level":5,"score":0.4833502471446991},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4709267020225525},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3428534269332886},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.28453677892684937},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.24744433164596558},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2175476849079132},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18363621830940247},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.13182/fst12-a14626","doi":"https://doi.org/10.13182/fst12-a14626","is_oa":false,"landing_page_url":"https://doi.org/10.13182/fst12-a14626","pdf_url":null,"source":{"id":"https://openalex.org/S104092111","display_name":"Fusion Science & Technology","issn_l":"1536-1055","issn":["1536-1055","1943-7641"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-70","russia-white-list-2"],"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547","https://openalex.org/P4310320449"],"host_organization_lineage_names":["Taylor & Francis","Informa"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fusion Science and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321992","display_name":"Minist\u00e9rio da Ci\u00eancia, Tecnologia e Inova\u00e7\u00e3o","ror":"https://ror.org/050zdnc69"},{"id":"https://openalex.org/F4320322930","display_name":"Ministerio de Ciencia e Innovaci\u00f3n","ror":null},{"id":"https://openalex.org/F4320323737","display_name":"Ministerio de Ciencia y Tecnolog\u00eda","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1513874326","https://openalex.org/W1528361845","https://openalex.org/W1553262910","https://openalex.org/W1661212201","https://openalex.org/W1920296222","https://openalex.org/W1980542004","https://openalex.org/W1980950130","https://openalex.org/W1981097774","https://openalex.org/W1989445634","https://openalex.org/W2026787118","https://openalex.org/W2080021732","https://openalex.org/W2085989833","https://openalex.org/W2102297952","https://openalex.org/W2115755118","https://openalex.org/W2117112756","https://openalex.org/W2138517257","https://openalex.org/W2139709458","https://openalex.org/W2145452316","https://openalex.org/W2151023586","https://openalex.org/W2160006420","https://openalex.org/W2477850881","https://openalex.org/W2903158431","https://openalex.org/W4233518571","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W4312294904"],"related_works":["https://openalex.org/W6974064433","https://openalex.org/W3000008842","https://openalex.org/W3021963124","https://openalex.org/W2167360450","https://openalex.org/W2767988841","https://openalex.org/W3002791897","https://openalex.org/W4360982337","https://openalex.org/W1998191174","https://openalex.org/W4417514334","https://openalex.org/W6959531821"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,32,62,70,95,100,109,114,118,127,135,138,141,158,165],"problem":[4,89],"of":[5,35,39,99,117,123,130,137],"finding":[6],"a":[7,43,86,131],"minimal":[8],"and":[9,22],"good":[10],"enough":[11],"training":[12,36,124],"data":[13],"set":[14],"for":[15,53,78],"classification":[16,88],"purposes":[17],"by":[18,112],"using":[19],"active":[20,49,121],"learning":[21,26,50],"conformal":[23,73,132],"predictors.":[24],"Active":[25],"means":[27],"to":[28,59,107,145],"have":[29,75,161],"control":[30],"in":[31,42,57,85,157],"selection":[33,55,122],"process":[34],"samples":[37,63],"instead":[38],"choosing":[40],"them":[41],"random":[44],"way.":[45],"To":[46],"this":[47],"end,":[48],"methodologies":[51],"look":[52],"establishing":[54],"criteria":[56],"order":[58],"find":[60],"out":[61],"that":[64],"show":[65],"better":[66],"discrimination":[67],"capabilities.":[68],"In":[69],"present":[71],"case,":[72],"predictors":[74],"been":[76,162],"used":[77,163],"these":[79],"purposes.":[80],"Results":[81],"will":[82],"be":[83],"presented":[84],"five-class":[87],"with":[90],"images.":[91,119],"The":[92,120],"features":[93],"are":[94],"vertical":[96],"detail":[97],"coefficients":[98],"Haar":[101],"wavelet":[102],"transform":[103],"at":[104],"level":[105],"four":[106],"diminish":[108],"sample":[110],"dimensionality":[111],"reducing":[113],"spatial":[115],"redundancy":[116],"sets":[125],"(through":[126],"reliability":[128],"measures":[129],"predictor)":[133],"allows":[134],"improvement":[136],"classifiers.":[139,167],"Here,":[140],"word":[142],"\u201cimprovement\u201d":[143],"refers":[144],"obtaining":[146],"higher":[147],"generalization":[148],"properties":[149],"thereby":[150],"avoiding":[151],"overfitting.":[152],"Support":[153],"vector":[154],"machines":[155],"classifiers,":[156],"one-versus-the-rest":[159],"approach,":[160],"as":[164],"underlying":[166]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}
