{"id":"https://openalex.org/W2409400487","doi":"https://doi.org/10.1109/lgrs.2016.2557315","title":"One-Class Gaussian Process for Possibilistic Classification Using Imaging Spectroscopy","display_name":"One-Class Gaussian Process for Possibilistic Classification Using Imaging Spectroscopy","publication_year":2016,"publication_date":"2016-06-02","ids":{"openalex":"https://openalex.org/W2409400487","doi":"https://doi.org/10.1109/lgrs.2016.2557315","mag":"2409400487"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2016.2557315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2016.2557315","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/A5102766902","display_name":"Leila Kalantari","orcid":"https://orcid.org/0000-0001-6824-1714"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leila Kalantari","raw_affiliation_strings":["Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA"],"raw_orcid":"https://orcid.org/0000-0001-6824-1714","affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057277525","display_name":"Paul Gader","orcid":"https://orcid.org/0000-0001-6276-9403"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paul Gader","raw_affiliation_strings":["Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028916813","display_name":"Sarah Graves","orcid":"https://orcid.org/0000-0003-3805-4242"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sarah Graves","raw_affiliation_strings":["School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071762860","display_name":"Stephanie Bohlman","orcid":"https://orcid.org/0000-0002-4935-7321"},"institutions":[{"id":"https://openalex.org/I33213144","display_name":"University of Florida","ror":"https://ror.org/02y3ad647","country_code":"US","type":"education","lineage":["https://openalex.org/I33213144"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Stephanie A. Bohlman","raw_affiliation_strings":["School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA","institution_ids":["https://openalex.org/I33213144"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.474,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64260113,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"13","issue":"7","first_page":"967","last_page":"971"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11871","display_name":"Advanced Statistical Methods and Models","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9857000112533569,"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/support-vector-machine","display_name":"Support vector machine","score":0.8189548254013062},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7412123680114746},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7305407524108887},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6986913681030273},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5837215781211853},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5744229555130005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5658898949623108},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5450322031974792},{"id":"https://openalex.org/keywords/probabilistic-classification","display_name":"Probabilistic classification","score":0.5035812258720398},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.47507208585739136},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4673493206501007},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45356154441833496},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4210054278373718},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36298707127571106},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.16895762085914612}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8189548254013062},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7412123680114746},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7305407524108887},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6986913681030273},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5837215781211853},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5744229555130005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5658898949623108},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5450322031974792},{"id":"https://openalex.org/C189119545","wikidata":"https://www.wikidata.org/wiki/Q5128022","display_name":"Probabilistic classification","level":4,"score":0.5035812258720398},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.47507208585739136},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4673493206501007},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45356154441833496},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4210054278373718},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36298707127571106},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.16895762085914612},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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":1,"locations":[{"id":"doi:10.1109/lgrs.2016.2557315","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2016.2557315","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"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.7599999904632568}],"awards":[{"id":"https://openalex.org/G8259931792","display_name":null,"funder_award_id":"-0752017","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1597739853","https://openalex.org/W1746819321","https://openalex.org/W1905898145","https://openalex.org/W1970088130","https://openalex.org/W1972978214","https://openalex.org/W1985291094","https://openalex.org/W1990421832","https://openalex.org/W1997592224","https://openalex.org/W2027144818","https://openalex.org/W2065255264","https://openalex.org/W2101709642","https://openalex.org/W2104269704","https://openalex.org/W2107386393","https://openalex.org/W2112129724","https://openalex.org/W2117063635","https://openalex.org/W2119821739","https://openalex.org/W2122441658","https://openalex.org/W2134601045","https://openalex.org/W2136251662","https://openalex.org/W2147590979","https://openalex.org/W2153534417","https://openalex.org/W2153635508","https://openalex.org/W2169535263","https://openalex.org/W2326588846","https://openalex.org/W4211049957","https://openalex.org/W4239510810","https://openalex.org/W4285719527","https://openalex.org/W6639709970","https://openalex.org/W6675823452"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2141609920","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W4286748465","https://openalex.org/W3118984993","https://openalex.org/W2144336328","https://openalex.org/W3196933554"],"abstract_inverted_index":{"With":[0],"the":[1,12,39,51,81,91,120],"greater":[2],"availability":[3],"of":[4,14,38,47,66],"imaging":[5],"spectrometer":[6],"data,":[7],"vegetation":[8],"species":[9],"classification":[10,78,112],"in":[11],"presence":[13],"outlier":[15,139],"and":[16,23,68,90,99,134],"ambiguous":[17],"spectra":[18,34],"is":[19,42,50,55],"an":[20,56],"increasingly":[21],"important":[22],"poorly":[24],"addressed":[25],"problem.":[26],"At":[27],"large":[28],"scales,":[29],"assuming":[30],"that":[31,62],"all":[32],"test":[33],"are":[35,97],"from":[36],"one":[37],"training":[40],"classes":[41],"unrealistic.":[43],"An":[44],"attractive":[45],"resolution":[46],"these":[48],"problems":[49],"possibility":[52],"theory,":[53,61],"which":[54],"axiomatic":[57],"system,":[58],"like":[59],"probability":[60],"represents":[63],"uncertain":[64],"labels":[65],"outliers":[67],"ambiguities":[69],"more":[70],"flexibly.":[71],"In":[72],"this":[73],"letter,":[74],"two":[75,127],"popular":[76],"probabilistic":[77],"algorithms,":[79],"namely,":[80],"support":[82],"vector":[83],"machine":[84],"(SVM)":[85],"with":[86,113,126,138],"Platt":[87],"scaling":[88],"(SVM-Platt)":[89],"Gaussian":[92],"process":[93],"(GP)":[94],"classifier":[95],"(GPC),":[96],"evaluated":[98],"compared":[100],"to":[101],"a":[102],"novel":[103],"one-class":[104,111,117],"GP":[105],"(OCGP)":[106],"possibilistic":[107],"classifier.":[108],"OCGP,":[109],"unlike":[110],"GP,":[114],"another":[115],"GP-based":[116],"classifier,":[118],"finds":[119],"hyperparameters":[121],"automatically.":[122],"Experiments":[123],"were":[124],"conducted":[125],"data":[128],"sets.":[129],"The":[130],"OCGP":[131],"outperformed":[132],"SVM-Platt":[133],"GPC":[135],"when":[136],"tested":[137],"spectra.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}