{"id":"https://openalex.org/W2091938338","doi":"https://doi.org/10.1145/1014052.1016913","title":"Interactive training of advanced classifiers for mining remote sensing image archives","display_name":"Interactive training of advanced classifiers for mining remote sensing image archives","publication_year":2004,"publication_date":"2004-08-22","ids":{"openalex":"https://openalex.org/W2091938338","doi":"https://doi.org/10.1145/1014052.1016913","mag":"2091938338"},"language":"en","primary_location":{"id":"doi:10.1145/1014052.1016913","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1016913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5003826893","display_name":"Selim Aksoy","orcid":"https://orcid.org/0000-0003-4185-0565"},"institutions":[{"id":"https://openalex.org/I168864056","display_name":"Bilkent University","ror":"https://ror.org/02vh8a032","country_code":"TR","type":"education","lineage":["https://openalex.org/I168864056"]}],"countries":["TR"],"is_corresponding":true,"raw_author_name":"Selim Aksoy","raw_affiliation_strings":["Bilkent University, Bilkent, Ankara, Turkey"],"affiliations":[{"raw_affiliation_string":"Bilkent University, Bilkent, Ankara, Turkey","institution_ids":["https://openalex.org/I168864056"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109173865","display_name":"Krzysztof Koperski","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126054","display_name":"Strategic Insight (United States)","ror":"https://ror.org/0303r7956","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126054"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krzysztof Koperski","raw_affiliation_strings":["Insightful Corporation, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Insightful Corporation, Seattle, WA","institution_ids":["https://openalex.org/I4210126054"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033026453","display_name":"Carsten Tusk","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126054","display_name":"Strategic Insight (United States)","ror":"https://ror.org/0303r7956","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126054"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carsten Tusk","raw_affiliation_strings":["Insightful Corporation, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Insightful Corporation, Seattle, WA","institution_ids":["https://openalex.org/I4210126054"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049009088","display_name":"Giovanni Marchisio","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126054","display_name":"Strategic Insight (United States)","ror":"https://ror.org/0303r7956","country_code":"US","type":"company","lineage":["https://openalex.org/I4210126054"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Giovanni Marchisio","raw_affiliation_strings":["Insightful Corporation, Seattle, WA"],"affiliations":[{"raw_affiliation_string":"Insightful Corporation, Seattle, WA","institution_ids":["https://openalex.org/I4210126054"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5003826893"],"corresponding_institution_ids":["https://openalex.org/I168864056"],"apc_list":null,"apc_paid":null,"fwci":1.6563,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.84952244,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"773","last_page":"782"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9869999885559082,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9869999885559082,"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/T11490","display_name":"Hydrological Forecasting Using AI","score":0.9850000143051147,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9821000099182129,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7836017608642578},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.6743391156196594},{"id":"https://openalex.org/keywords/categorical-variable","display_name":"Categorical variable","score":0.6389813423156738},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5593316555023193},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5235040783882141},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.4872852563858032},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4406942129135132},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.43708962202072144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3216894865036011},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2968405485153198},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.25348544120788574},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.1578255593776703},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09702825546264648},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09522038698196411}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7836017608642578},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.6743391156196594},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.6389813423156738},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5593316555023193},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5235040783882141},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.4872852563858032},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4406942129135132},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.43708962202072144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3216894865036011},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2968405485153198},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.25348544120788574},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.1578255593776703},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09702825546264648},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09522038698196411},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1014052.1016913","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1016913","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.bilkent.edu.tr:11693/27426","is_oa":false,"landing_page_url":"http://hdl.handle.net/11693/27426","pdf_url":null,"source":{"id":"https://openalex.org/S4306400079","display_name":"Bilkent University Institutional Repository (Bilkent University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I168864056","host_organization_name":"Bilkent University","host_organization_lineage":["https://openalex.org/I168864056"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"KDD '04 Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5449017812","display_name":null,"funder_award_id":"unknown","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"}],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W66342537","https://openalex.org/W147723833","https://openalex.org/W1504694836","https://openalex.org/W1564419782","https://openalex.org/W1594031697","https://openalex.org/W1906553994","https://openalex.org/W1962265951","https://openalex.org/W2042385018","https://openalex.org/W2044758663","https://openalex.org/W2100714408","https://openalex.org/W2124353687","https://openalex.org/W2124624125","https://openalex.org/W2125148312","https://openalex.org/W2138973109","https://openalex.org/W2186263394","https://openalex.org/W2537113732","https://openalex.org/W2799061466","https://openalex.org/W3197494818","https://openalex.org/W4205687621","https://openalex.org/W4285719527","https://openalex.org/W4297204443","https://openalex.org/W6721667826","https://openalex.org/W6843735874","https://openalex.org/W6981165577","https://openalex.org/W6990029666","https://openalex.org/W7014191107"],"related_works":["https://openalex.org/W4386799044","https://openalex.org/W2773208253","https://openalex.org/W2560646951","https://openalex.org/W4297454206","https://openalex.org/W65104662","https://openalex.org/W1871748041","https://openalex.org/W2362286668","https://openalex.org/W2074219825","https://openalex.org/W2043913960","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Advances":[0],"in":[1],"satellite":[2],"technology":[3],"and":[4,22,54,83,105,110,144,164,166,186,201,206],"availability":[5],"of":[6,13,33,79,85,124,134,156,204,208],"down-loaded":[7],"images":[8,205],"constantly":[9],"increase":[10],"the":[11,31,119,122,132,154,172],"sizes":[12],"remote":[14,35,63,209],"sensing":[15,36,64,210],"image":[16,60,65,86,211],"archives.":[17,87,212],"Automatic":[18],"content":[19],"extraction,":[20],"classification":[21],"content-based":[23],"retrieval":[24],"have":[25],"become":[26],"highly":[27],"desired":[28],"goals":[29],"for":[30,41,76,94,131,182,197],"development":[32],"intelligent":[34],"databases.":[37],"The":[38],"common":[39],"approach":[40],"mining":[42,84,207],"these":[43],"databases":[44],"uses":[45,72],"rules":[46],"created":[47],"by":[48],"analysts.":[49],"However,":[50],"incorporating":[51],"GIS":[52,147],"information":[53],"human":[55],"expert":[56],"knowledge":[57],"with":[58,158],"digital":[59],"processing":[61],"improves":[62],"analysis.":[66],"We":[67],"developed":[68],"a":[69,91],"system":[70],"that":[71,191],"decision":[73,192],"tree":[74],"classifiers":[75],"interactive":[77],"learning":[78],"land":[80],"cover":[81],"models":[82],"Decision":[88],"trees":[89,193],"provide":[90,194],"promising":[92],"solution":[93],"this":[95],"problem":[96],"because":[97],"they":[98,111],"can":[99],"operate":[100],"on":[101],"both":[102,162,199],"numerical":[103],"(continuous)":[104],"categorical":[106],"(discrete)":[107],"data":[108,143,160],"sources,":[109],"do":[112,179],"not":[113,180],"require":[114],"any":[115],"assumptions":[116],"about":[117],"neither":[118],"distributions":[120],"nor":[121],"independence":[123],"attribute":[125],"values.":[126],"This":[127],"is":[128],"especially":[129],"important":[130],"fusion":[133],"measurements":[135,178],"from":[136],"different":[137],"sources":[138],"like":[139],"spectral":[140],"data,":[141],"DEM":[142],"other":[145],"ancillary":[146],"data.":[148],"Furthermore,":[149],"using":[150],"surrogate":[151],"splits":[152],"provides":[153],"capability":[155],"dealing":[157],"missing":[159],"during":[161],"training":[163],"classification,":[165],"enables":[167],"handling":[168],"instrument":[169],"malfunctions":[170],"or":[171,176],"cases":[173],"where":[174],"one":[175],"more":[177],"exist":[181],"some":[183],"locations.":[184],"Quantitative":[185],"qualitative":[187],"performance":[188],"evaluation":[189],"showed":[190],"powerful":[195],"tools":[196],"modeling":[198],"pixel":[200],"region":[202],"contents":[203]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
