{"id":"https://openalex.org/W4383428395","doi":"https://doi.org/10.1109/tgrs.2023.3292929","title":"One-Class Risk Estimation for One-Class Hyperspectral Image Classification","display_name":"One-Class Risk Estimation for One-Class Hyperspectral Image Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4383428395","doi":"https://doi.org/10.1109/tgrs.2023.3292929"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3292929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3292929","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/A5035641804","display_name":"Hengwei Zhao","orcid":"https://orcid.org/0000-0001-5878-5152"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hengwei Zhao","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5878-5152","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100754351","display_name":"Yanfei Zhong","orcid":"https://orcid.org/0000-0001-9446-5850"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanfei Zhong","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-9446-5850","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100352781","display_name":"Xinyu Wang","orcid":"https://orcid.org/0000-0002-0493-3954"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu Wang","raw_affiliation_strings":["School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0493-3954","affiliations":[{"raw_affiliation_string":"School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016558583","display_name":"Hong Shu","orcid":"https://orcid.org/0000-0003-2108-1797"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]},{"id":"https://openalex.org/I4210118728","display_name":"State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing","ror":"https://ror.org/02bpap860","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210118728"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Shu","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-2108-1797","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747","https://openalex.org/I4210118728"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7499,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70805801,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9818000197410583,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9279000163078308,"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/overfitting","display_name":"Overfitting","score":0.8689969182014465},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7997103929519653},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6537504196166992},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6173121333122253},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6059800386428833},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.595426619052887},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5859413146972656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5643554925918579},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5536426901817322},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46265465021133423},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4466104507446289},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4443493187427521},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3982229232788086},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2717124819755554},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18119925260543823},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15149378776550293}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8689969182014465},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7997103929519653},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6537504196166992},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6173121333122253},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6059800386428833},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.595426619052887},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5859413146972656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5643554925918579},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5536426901817322},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46265465021133423},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4466104507446289},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4443493187427521},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3982229232788086},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2717124819755554},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18119925260543823},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15149378776550293}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3292929","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3292929","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"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1223461643","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u5f71\u50cf\u6df1\u5ea6\u975e\u7ebf\u6027\u4e9a\u50cf\u5143\u5236\u56fe\u65b9\u6cd5\u7814\u7a76","funder_award_id":"42071350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2040895979","display_name":null,"funder_award_id":"2022YFB3903502","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6245942927","display_name":null,"funder_award_id":"42101327","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1861993554","https://openalex.org/W2029316659","https://openalex.org/W2087556827","https://openalex.org/W2105497548","https://openalex.org/W2123958887","https://openalex.org/W2124431629","https://openalex.org/W2131651374","https://openalex.org/W2134510195","https://openalex.org/W2137420707","https://openalex.org/W2144182447","https://openalex.org/W2147280166","https://openalex.org/W2194775991","https://openalex.org/W2411643563","https://openalex.org/W2466501638","https://openalex.org/W2564563592","https://openalex.org/W2609880332","https://openalex.org/W2732412926","https://openalex.org/W2766862779","https://openalex.org/W2770853283","https://openalex.org/W2800371750","https://openalex.org/W2884561390","https://openalex.org/W2884585870","https://openalex.org/W2888119354","https://openalex.org/W2893127089","https://openalex.org/W2921445432","https://openalex.org/W2948763898","https://openalex.org/W2950185713","https://openalex.org/W2970565181","https://openalex.org/W2971432438","https://openalex.org/W2979585146","https://openalex.org/W3006984222","https://openalex.org/W3008189420","https://openalex.org/W3049655825","https://openalex.org/W3089037376","https://openalex.org/W3100826601","https://openalex.org/W3101640299","https://openalex.org/W3119997721","https://openalex.org/W3125860323","https://openalex.org/W3137839916","https://openalex.org/W3139745482","https://openalex.org/W3156696558","https://openalex.org/W3170347305","https://openalex.org/W3182256037","https://openalex.org/W3186597588","https://openalex.org/W3201461236","https://openalex.org/W3213181250","https://openalex.org/W3213734590","https://openalex.org/W4205124618","https://openalex.org/W4220853886","https://openalex.org/W4221065202","https://openalex.org/W4225688999","https://openalex.org/W4229457118","https://openalex.org/W4280563105","https://openalex.org/W4281633835","https://openalex.org/W4283760989","https://openalex.org/W4285124290","https://openalex.org/W4285505669","https://openalex.org/W4292550292","https://openalex.org/W4312796128","https://openalex.org/W4312845279","https://openalex.org/W4321484009","https://openalex.org/W4361278435","https://openalex.org/W4365420606","https://openalex.org/W6639315830","https://openalex.org/W6720067423","https://openalex.org/W6746138342","https://openalex.org/W6774637898","https://openalex.org/W6804773651","https://openalex.org/W6842031431","https://openalex.org/W6851355473"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W4378678253","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W2964843961","https://openalex.org/W3010730661"],"abstract_inverted_index":{"Hyperspectral":[0],"imagery":[1],"(HSI)":[2],"one-class":[3,32,85,95],"classification":[4,33,121],"is":[5,37],"aimed":[6],"at":[7],"identifying":[8],"a":[9,43,90,100],"single":[10],"target":[11],"class":[12,120],"from":[13],"the":[14,26,46,55,69,109,116,123,138,141],"HSI":[15,76,84,94],"by":[16],"using":[17],"only":[18],"knowing":[19],"positive":[20,51],"data,":[21],"which":[22],"can":[23],"significantly":[24],"reduce":[25],"requirements":[27],"for":[28,39],"annotation.":[29],"However,":[30],"when":[31],"meets":[34],"HSI,":[35],"it":[36],"difficult":[38],"classifiers":[40],"to":[41,54,71,107,136],"find":[42],"balance":[44],"between":[45],"overfitting":[47],"and":[48,60],"underfitting":[49],"of":[50,57,118,125,140],"data":[52],"due":[53],"problems":[56],"distribution":[58,61,73,126],"overlap":[59,74],"imbalance.":[62,127],"Although":[63],"deep":[64,82,93],"learning-based":[65,83],"methods":[66],"are":[67],"currently":[68],"mainstream":[70],"overcome":[72],"in":[75,122,132],"multi-classificaiton,":[77],"few":[78],"researches":[79],"focus":[80],"on":[81],"classification.":[86],"In":[87],"this":[88],"paper,":[89],"weakly":[91],"supervised":[92],"classifier,":[96],"namelyHOneClsis":[97],"proposed,":[98],"where":[99],"risk":[101],"estimator\u2014theOne-Class":[102],"Risk":[103],"Estimator\u2014is":[104],"particularly":[105],"introduced":[106],"make":[108],"full":[110],"convolutional":[111],"neural":[112],"network":[113],"(FCN)":[114],"with":[115],"ability":[117],"one":[119],"case":[124],"Extensive":[128],"experiments":[129],"(20":[130],"tasks":[131],"total)":[133],"were":[134],"conducted":[135],"demonstrate":[137],"superiority":[139],"proposed":[142],"classifier.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}
