{"id":"https://openalex.org/W2036150674","doi":"https://doi.org/10.1109/lgrs.2011.2172770","title":"A Batch-Mode Active Learning Technique Based on Multiple Uncertainty for SVM Classifier","display_name":"A Batch-Mode Active Learning Technique Based on Multiple Uncertainty for SVM Classifier","publication_year":2011,"publication_date":"2011-12-02","ids":{"openalex":"https://openalex.org/W2036150674","doi":"https://doi.org/10.1109/lgrs.2011.2172770","mag":"2036150674"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2011.2172770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2011.2172770","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5035487111","display_name":"Swarnajyoti Patra","orcid":"https://orcid.org/0000-0003-4300-9307"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Swarnajyoti Patra","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","Department of Information Engineering and Computer Science, University of Trento , Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento , Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006095323","display_name":"Lorenzo Bruzzone","orcid":"https://orcid.org/0000-0002-6036-459X"},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Lorenzo Bruzzone","raw_affiliation_strings":["Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","Department of Information Engineering and Computer Science, University of Trento , Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento, Trento, Italy","institution_ids":["https://openalex.org/I193223587"]},{"raw_affiliation_string":"Department of Information Engineering and Computer Science, University of Trento , Trento, Italy","institution_ids":["https://openalex.org/I193223587"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193223587"],"apc_list":null,"apc_paid":null,"fwci":6.4709,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.96472891,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":"3","first_page":"497","last_page":"501"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9943000078201294,"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":0.9943000078201294,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9764999747276306,"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/T10057","display_name":"Face and Expression Recognition","score":0.9721999764442444,"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/medoid","display_name":"Medoid","score":0.7257562279701233},{"id":"https://openalex.org/keywords/hyperplane","display_name":"Hyperplane","score":0.6631128787994385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6448440551757812},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6388803720474243},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.585043728351593},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5656987428665161},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5553544759750366},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.4850451350212097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47406095266342163},{"id":"https://openalex.org/keywords/multiclass-classification","display_name":"Multiclass classification","score":0.4498514235019684},{"id":"https://openalex.org/keywords/batch-processing","display_name":"Batch processing","score":0.4446215331554413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42517584562301636},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37559372186660767},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31542104482650757}],"concepts":[{"id":"https://openalex.org/C63085389","wikidata":"https://www.wikidata.org/wiki/Q4287912","display_name":"Medoid","level":3,"score":0.7257562279701233},{"id":"https://openalex.org/C68693459","wikidata":"https://www.wikidata.org/wiki/Q657586","display_name":"Hyperplane","level":2,"score":0.6631128787994385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6448440551757812},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6388803720474243},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.585043728351593},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5656987428665161},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5553544759750366},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.4850451350212097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47406095266342163},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.4498514235019684},{"id":"https://openalex.org/C172658912","wikidata":"https://www.wikidata.org/wiki/Q661613","display_name":"Batch processing","level":2,"score":0.4446215331554413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42517584562301636},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37559372186660767},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31542104482650757},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lgrs.2011.2172770","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2011.2172770","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/88676","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/88676","pdf_url":null,"source":{"id":"https://openalex.org/S4377196320","display_name":"Iris (University of Trento)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I193223587","host_organization_name":"University of Trento","host_organization_lineage":["https://openalex.org/I193223587"],"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":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.6100000143051147,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1845402413","https://openalex.org/W2087347434","https://openalex.org/W2098758111","https://openalex.org/W2114691401","https://openalex.org/W2125782835","https://openalex.org/W2129932701","https://openalex.org/W2134663338","https://openalex.org/W2136251662","https://openalex.org/W2139212933","https://openalex.org/W2139573966","https://openalex.org/W2148275879","https://openalex.org/W2150045166","https://openalex.org/W2570764145","https://openalex.org/W2949071206","https://openalex.org/W4285719527","https://openalex.org/W6638701278"],"related_works":["https://openalex.org/W2369655046","https://openalex.org/W3133849001","https://openalex.org/W2019467317","https://openalex.org/W2022056881","https://openalex.org/W1585519779","https://openalex.org/W2081066201","https://openalex.org/W1965515989","https://openalex.org/W4376167435","https://openalex.org/W2088737283","https://openalex.org/W1999587863"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"we":[3],"present":[4],"a":[5,37,109],"novel":[6],"batch-mode":[7,173],"active":[8,174],"learning":[9,175],"technique":[10],"for":[11,158],"solving":[12],"multiclass":[13],"classification":[14],"problems":[15],"by":[16,35,168],"using":[17],"the":[18,24,43,47,55,61,65,81,84,88,97,123,127,132,143,149,163,179,191,194],"support":[19],"vector":[20],"machine":[21],"classifier":[22],"with":[23,171],"one-against-all":[25],"architecture.":[26],"The":[27,160],"uncertainty":[28],"of":[29,67,74,87,99,102,112,145,162,193],"each":[30,119,154],"unlabeled":[31],"sample":[32,62,151],"is":[33,63,140,156,166],"measured":[34],"defining":[36],"criterion":[38],"which":[39],"not":[40],"only":[41],"considers":[42],"smallest":[44],"distance":[45],"to":[46,57,142],"decision":[48,69,82],"hyperplanes":[49,59],"but":[50],"also":[51],"takes":[52],"into":[53,92],"account":[54],"distances":[56],"other":[58,172],"if":[60],"within":[64],"margin":[66],"their":[68],"boundaries.":[70],"To":[71,121],"select":[72],"batch":[73],"most":[75,113],"uncertain":[76,85,114,146],"samples":[77,115],"from":[78,118,153],"all":[79],"over":[80],"region,":[83],"regions":[86],"classifiers":[89,104],"are":[90,116],"partitioned":[91],"multiple":[93],"parts":[94],"depending":[95],"on":[96,106,183],"number":[98,111],"geometrical":[100],"margins":[101],"binary":[103],"passing":[105],"them.":[107],"Then,":[108],"balanced":[110],"selected":[117,157],"part.":[120],"minimize":[122],"redundancy":[124],"and":[125,148],"keep":[126],"diversity":[128],"among":[129],"these":[130],"samples,":[131,147],"kernel":[133],"<i":[134],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[135],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">k</i>":[136],"-means":[137],"clustering":[138],"algorithm":[139],"applied":[141],"set":[144],"representative":[150],"(medoid)":[152],"cluster":[155],"labeling.":[159],"effectiveness":[161,192],"proposed":[164,195],"method":[165],"evaluated":[167],"comparing":[169],"it":[170],"techniques":[176],"existing":[177],"in":[178],"literature.":[180],"Experimental":[181],"results":[182],"two":[184],"different":[185],"remote":[186],"sensing":[187],"data":[188],"sets":[189],"confirmed":[190],"technique.":[196]},"counts_by_year":[{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":2}],"updated_date":"2026-07-02T09:51:11.867554","created_date":"2025-10-10T00:00:00"}
