{"id":"https://openalex.org/W1974914315","doi":"https://doi.org/10.1109/tgrs.2011.2174246","title":"Improved Estimation of Water Chlorophyll Concentration With Semisupervised Gaussian Process Regression","display_name":"Improved Estimation of Water Chlorophyll Concentration With Semisupervised Gaussian Process Regression","publication_year":2012,"publication_date":"2012-01-04","ids":{"openalex":"https://openalex.org/W1974914315","doi":"https://doi.org/10.1109/tgrs.2011.2174246","mag":"1974914315"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2011.2174246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2011.2174246","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5054237841","display_name":"Yakoub Bazi","orcid":"https://orcid.org/0000-0001-9287-0596"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Yakoub Bazi","raw_affiliation_strings":["Advanced Laboratory for Intelligent Systems Research, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","Adv. Lab. for Intell. Syst. Res., King Saud Univ., Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Advanced Laboratory for Intelligent Systems Research, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]},{"raw_affiliation_string":"Adv. Lab. for Intell. Syst. Res., King Saud Univ., Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052594698","display_name":"Naif Alajlan","orcid":"https://orcid.org/0000-0003-1846-1131"},"institutions":[{"id":"https://openalex.org/I28022161","display_name":"King Saud University","ror":"https://ror.org/02f81g417","country_code":"SA","type":"education","lineage":["https://openalex.org/I28022161"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Naif Alajlan","raw_affiliation_strings":["Advanced Laboratory for Intelligent Systems Research, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","Adv. Lab. for Intell. Syst. Res., King Saud Univ., Riyadh, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"Advanced Laboratory for Intelligent Systems Research, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]},{"raw_affiliation_string":"Adv. Lab. for Intell. Syst. Res., King Saud Univ., Riyadh, Saudi Arabia","institution_ids":["https://openalex.org/I28022161"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021389231","display_name":"Farid Melgani","orcid":"https://orcid.org/0000-0001-9745-3732"},"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":"Farid Melgani","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"],"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":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054237841"],"corresponding_institution_ids":["https://openalex.org/I28022161"],"apc_list":null,"apc_paid":null,"fwci":3.0379,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.90455021,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"50","issue":"7","first_page":"2733","last_page":"2743"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9966999888420105,"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/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9930999875068665,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6488631963729858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5932196974754333},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5541285872459412},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.531064510345459},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5093613862991333},{"id":"https://openalex.org/keywords/regression-analysis","display_name":"Regression analysis","score":0.4635882079601288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46347129344940186},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.4551047086715698},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42454013228416443},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4128879904747009},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4103318750858307},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.36903834342956543},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.33986765146255493},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.304848849773407}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6488631963729858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5932196974754333},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5541285872459412},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.531064510345459},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5093613862991333},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.4635882079601288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46347129344940186},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4551047086715698},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42454013228416443},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4128879904747009},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4103318750858307},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36903834342956543},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.33986765146255493},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.304848849773407},{"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":2,"locations":[{"id":"doi:10.1109/tgrs.2011.2174246","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2011.2174246","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:iris.unitn.it:11572/88945","is_oa":false,"landing_page_url":"http://hdl.handle.net/11572/88945","pdf_url":null,"source":{"id":"https://openalex.org/S4306401913","display_name":"Institutional Research Information System (Universit\u00e0 degli Studi di 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/6","score":0.8600000143051147,"display_name":"Clean water and sanitation"}],"awards":[],"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":34,"referenced_works":["https://openalex.org/W1515272691","https://openalex.org/W1553373771","https://openalex.org/W1564026136","https://openalex.org/W1595498733","https://openalex.org/W1905898145","https://openalex.org/W1976426738","https://openalex.org/W2008499862","https://openalex.org/W2044774029","https://openalex.org/W2072555316","https://openalex.org/W2076392573","https://openalex.org/W2085824658","https://openalex.org/W2100835628","https://openalex.org/W2107152312","https://openalex.org/W2113381057","https://openalex.org/W2115408897","https://openalex.org/W2117063635","https://openalex.org/W2126105956","https://openalex.org/W2128973832","https://openalex.org/W2134601045","https://openalex.org/W2135622155","https://openalex.org/W2139095875","https://openalex.org/W2140939548","https://openalex.org/W2141193993","https://openalex.org/W2143381319","https://openalex.org/W2145539952","https://openalex.org/W2150046657","https://openalex.org/W2156418736","https://openalex.org/W2158006878","https://openalex.org/W2159602351","https://openalex.org/W2165171393","https://openalex.org/W2169027522","https://openalex.org/W4244494905","https://openalex.org/W4292408320","https://openalex.org/W6639709970"],"related_works":["https://openalex.org/W4389055065","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4300066510","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W4293503520","https://openalex.org/W3134152097","https://openalex.org/W4311388919","https://openalex.org/W2048488252"],"abstract_inverted_index":{"This":[0,19],"paper":[1],"proposes":[2],"a":[3],"novel":[4],"semisupervised":[5],"regression":[6,67],"framework":[7,20],"for":[8,28,64],"estimating":[9],"chlorophyll":[10],"concentrations":[11],"in":[12,50,103],"subsurface":[13],"waters":[14],"from":[15,59],"remotely":[16],"sensed":[17],"imagery.":[18],"integrates":[21],"multiobjective":[22],"optimization":[23,83],"and":[24,111,127,174,185,191],"Gaussian":[25],"processes":[26],"(GPs)":[27],"boosting":[29],"the":[30,33,45,60,66,72,81,89,93,99,106,112,115,124,128,137,144,158,166,171,175],"accuracy":[31],"of":[32,71,74,84,92,105,152],"estimation":[34,70,145],"process":[35,146],"when":[36],"conditioned":[37],"by":[38,80,170],"limited":[39],"labeled-sample":[40],"availability.":[41],"To":[42],"this":[43],"end,":[44],"labeled":[46],"samples":[47,77,154],"are":[48,155,163,189],"exploited":[49],"conjunction":[51],"with":[52],"unlabeled":[53,76,153],"ones":[54],"(available":[55],"at":[56],"zero":[57],"cost":[58],"image":[61],"under":[62],"analysis)":[63],"learning":[65],"model.":[68],"The":[69,96],"target":[73],"these":[75],"is":[78,98,114],"handled":[79],"simultaneous":[82],"two":[85,121,148],"different":[86,149],"criteria":[87],"expressing":[88,123],"generalization":[90],"capabilities":[91],"GP":[94,172],"estimator.":[95],"first":[97],"empirical":[100],"risk":[101],"quantified":[102],"terms":[104,122],"mean":[107],"square":[108],"error":[109],"measure,":[110,178],"second":[113],"log":[116],"marginal":[117],"likelihood,":[118],"which":[119],"merges":[120],"model":[125],"complexity":[126],"data":[129,187],"fit":[130],"capability,":[131],"respectively.":[132,179],"In":[133],"order":[134],"to":[135,142,157],"alleviate":[136],"computational":[138],"burden":[139],"and,":[140],"possibly,":[141],"improve":[143],"accuracy,":[147],"selection":[150],"strategies":[151],"compared":[156],"simple":[159],"random-sampling":[160],"procedure.":[161],"They":[162],"based":[164],"on":[165,183],"estimated":[167],"variance":[168],"provided":[169],"estimator":[173],"differential":[176],"entropy":[177],"Experimental":[180],"results":[181],"obtained":[182],"simulated":[184],"real":[186],"sets":[188],"reported":[190],"discussed.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}