{"id":"https://openalex.org/W2763736326","doi":"https://doi.org/10.3390/rs9101041","title":"Exploring the Potential of Active Learning for Automatic Identification of Marine Oil Spills Using 10-Year (2004\u20132013) RADARSAT Data","display_name":"Exploring the Potential of Active Learning for Automatic Identification of Marine Oil Spills Using 10-Year (2004\u20132013) RADARSAT Data","publication_year":2017,"publication_date":"2017-10-13","ids":{"openalex":"https://openalex.org/W2763736326","doi":"https://doi.org/10.3390/rs9101041","mag":"2763736326"},"language":"en","primary_location":{"id":"doi:10.3390/rs9101041","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9101041","pdf_url":"https://www.mdpi.com/2072-4292/9/10/1041/pdf?version=1508221609","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/9/10/1041/pdf?version=1508221609","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100530825","display_name":"Yongfeng Cao","orcid":"https://orcid.org/0000-0003-4046-6254"},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yongfeng Cao","raw_affiliation_strings":["School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550001, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Computer Science, Guizhou Normal University, Guiyang 550001, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034166335","display_name":"Linlin Xu","orcid":"https://orcid.org/0000-0002-3488-5199"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]},{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CA","CN"],"is_corresponding":false,"raw_author_name":"Linlin Xu","raw_affiliation_strings":["School of Land Science and Technology, China University of Geosciences, Beijing 100083, China","Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada"],"affiliations":[{"raw_affiliation_string":"School of Land Science and Technology, China University of Geosciences, Beijing 100083, China","institution_ids":["https://openalex.org/I3125743391"]},{"raw_affiliation_string":"Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066149942","display_name":"David A. Clausi","orcid":"https://orcid.org/0000-0002-6383-0875"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"David Clausi","raw_affiliation_strings":["Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada"],"affiliations":[{"raw_affiliation_string":"Systems Design Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100530825"],"corresponding_institution_ids":["https://openalex.org/I154893126"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.6073,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.672,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"9","issue":"10","first_page":"1041","last_page":"1041"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12316","display_name":"Oil Spill Detection and Mitigation","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9535999894142151,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"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/T11698","display_name":"Underwater Acoustics Research","score":0.9330000281333923,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7191460132598877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6385689973831177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.637643575668335},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6162044405937195},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5584728121757507},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5367220044136047},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5268220901489258},{"id":"https://openalex.org/keywords/oil-spill","display_name":"Oil spill","score":0.5145663619041443},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.4593755006790161},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.435707151889801},{"id":"https://openalex.org/keywords/random-subspace-method","display_name":"Random subspace method","score":0.4256266951560974},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34507423639297485},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.12361729145050049}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7191460132598877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6385689973831177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.637643575668335},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6162044405937195},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5584728121757507},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5367220044136047},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5268220901489258},{"id":"https://openalex.org/C2985668151","wikidata":"https://www.wikidata.org/wiki/Q220187","display_name":"Oil spill","level":2,"score":0.5145663619041443},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.4593755006790161},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.435707151889801},{"id":"https://openalex.org/C106135958","wikidata":"https://www.wikidata.org/wiki/Q7291993","display_name":"Random subspace method","level":3,"score":0.4256266951560974},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34507423639297485},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.12361729145050049},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs9101041","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9101041","pdf_url":"https://www.mdpi.com/2072-4292/9/10/1041/pdf?version=1508221609","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3822b24f2fb6473396a01d23907c0e72","is_oa":true,"landing_page_url":"https://doaj.org/article/3822b24f2fb6473396a01d23907c0e72","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 9, Iss 10, p 1041 (2017)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/9/10/1041/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs9101041","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"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":"Remote Sensing; Volume 9; Issue 10; Pages: 1041","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs9101041","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs9101041","pdf_url":"https://www.mdpi.com/2072-4292/9/10/1041/pdf?version=1508221609","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.5}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G486668507","display_name":null,"funder_award_id":"41501410","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7841107101","display_name":null,"funder_award_id":"41161065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320319864","display_name":"ArcticNet","ror":"https://ror.org/01tca3t44"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320334436","display_name":"Canadian Space Agency","ror":"https://ror.org/03a1gte98"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2763736326.pdf","grobid_xml":"https://content.openalex.org/works/W2763736326.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W1510526001","https://openalex.org/W1573054556","https://openalex.org/W1588282782","https://openalex.org/W1678356000","https://openalex.org/W1963633096","https://openalex.org/W1972508834","https://openalex.org/W1973178306","https://openalex.org/W1976526581","https://openalex.org/W1990748933","https://openalex.org/W1995721042","https://openalex.org/W2000175358","https://openalex.org/W2004005279","https://openalex.org/W2006706121","https://openalex.org/W2009718124","https://openalex.org/W2010128473","https://openalex.org/W2016890032","https://openalex.org/W2021732807","https://openalex.org/W2028670389","https://openalex.org/W2041478093","https://openalex.org/W2043254690","https://openalex.org/W2044395236","https://openalex.org/W2048428751","https://openalex.org/W2053635778","https://openalex.org/W2060423551","https://openalex.org/W2063907334","https://openalex.org/W2068055385","https://openalex.org/W2070312459","https://openalex.org/W2079682096","https://openalex.org/W2081859028","https://openalex.org/W2088900896","https://openalex.org/W2089322632","https://openalex.org/W2091675249","https://openalex.org/W2097092275","https://openalex.org/W2101927381","https://openalex.org/W2103568877","https://openalex.org/W2106969041","https://openalex.org/W2108395474","https://openalex.org/W2117404342","https://openalex.org/W2118376687","https://openalex.org/W2124925761","https://openalex.org/W2126906809","https://openalex.org/W2129777864","https://openalex.org/W2133797090","https://openalex.org/W2134346724","https://openalex.org/W2134663338","https://openalex.org/W2135263224","https://openalex.org/W2137009733","https://openalex.org/W2139573966","https://openalex.org/W2146987667","https://openalex.org/W2149149727","https://openalex.org/W2151023586","https://openalex.org/W2158698691","https://openalex.org/W2159498975","https://openalex.org/W2159786793","https://openalex.org/W2263726068","https://openalex.org/W2546859874","https://openalex.org/W2787894218","https://openalex.org/W2903158431","https://openalex.org/W2911964244","https://openalex.org/W6630424276","https://openalex.org/W6654696195","https://openalex.org/W6683344514","https://openalex.org/W6756615331"],"related_works":["https://openalex.org/W4366990902","https://openalex.org/W2073883415","https://openalex.org/W4317732970","https://openalex.org/W4388550696","https://openalex.org/W4313289487","https://openalex.org/W4321636153","https://openalex.org/W3080944905","https://openalex.org/W2652414671","https://openalex.org/W1845209238","https://openalex.org/W2122938730"],"abstract_inverted_index":{"This":[0],"paper":[1],"intends":[2],"to":[3,61,72,119,137,156,169],"find":[4],"a":[5,89],"more":[6],"cost-effective":[7],"way":[8],"for":[9,80,174],"training":[10,160],"oil":[11,42],"spill":[12],"classification":[13,142],"systems":[14],"by":[15],"introducing":[16],"active":[17,65],"learning":[18],"(AL)":[19],"and":[20,44,54,88,110,123,128,192],"exploring":[21],"its":[22,151],"potential,":[23],"so":[24],"that":[25],"satisfying":[26],"classifiers":[27,98,127],"could":[28],"be":[29,170],"learned":[30],"with":[31,91,116,154,180],"reduced":[32],"number":[33],"of":[34,57,133,141,144,188,200,207],"labeled":[35],"samples.":[36,77],"The":[37,165,190],"dataset":[38],"used":[39],"has":[40],"143":[41],"spills":[43],"124":[45],"look-alikes":[46],"from":[47,59],"198":[48],"RADARSAT":[49],"images":[50],"covering":[51],"the":[52,74,85,121,171,177,198,201,208],"east":[53],"west":[55],"coasts":[56],"Canada":[58],"2004":[60],"2013.":[62],"Six":[63],"uncertainty-based":[64],"sample":[66,93],"selecting":[67],"(ACS)":[68],"methods":[69,118],"are":[70,95,114,135],"designed":[71],"choose":[73],"most":[75],"informative":[76],"A":[78],"method":[79,90],"reducing":[81],"information":[82],"redundancy":[83],"amongst":[84],"selected":[86],"samples":[87,161],"varying":[92],"preference":[94,125],"considered.":[96],"Four":[97],"(k-nearest":[99],"neighbor":[100],"(KNN),":[101],"support":[102],"vector":[103],"machine":[104],"(SVM),":[105],"linear":[106],"discriminant":[107],"analysis":[108],"(LDA)":[109],"decision":[111],"tree":[112],"(DT))":[113],"coupled":[115],"ACS":[117,129],"explore":[120],"interaction":[122],"possible":[124],"between":[126],"methods.":[130],"Three":[131],"kinds":[132,187],"measures":[134],"adopted":[136],"highlight":[138],"different":[139,163,186],"aspect":[140],"performance":[143,182,199],"these":[145],"AL-boosted":[146,202],"classifiers.":[147,210],"Overall,":[148],"AL":[149,178],"proves":[150],"strong":[152],"potential":[153],"4%":[155],"78%":[157],"reduction":[158],"on":[159],"in":[162,176,185],"settings.":[164],"SVM":[166,203],"classifier":[167,204],"shows":[168],"best":[172],"one":[173],"using":[175],"frame,":[179],"perfect":[181],"evolving":[183],"curves":[184],"measures.":[189],"exploration":[191],"exploitation":[193],"criterion":[194],"can":[195],"further":[196],"improve":[197],"but":[205],"not":[206],"other":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}
