{"id":"https://openalex.org/W1958291604","doi":"https://doi.org/10.1109/lgrs.2015.2475299","title":"Deep Learning Based Feature Selection for Remote Sensing Scene Classification","display_name":"Deep Learning Based Feature Selection for Remote Sensing Scene Classification","publication_year":2015,"publication_date":"2015-09-18","ids":{"openalex":"https://openalex.org/W1958291604","doi":"https://doi.org/10.1109/lgrs.2015.2475299","mag":"1958291604"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2015.2475299","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2475299","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/A5070093927","display_name":"Qin Zou","orcid":"https://orcid.org/0000-0001-7955-0782"},"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":true,"raw_author_name":"Qin Zou","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China","School of Computer Science, Wuhan University Wuhan China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University Wuhan China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008946246","display_name":"Lihao Ni","orcid":null},"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":"Lihao Ni","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China","School of Computer Science, Wuhan University Wuhan China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University Wuhan China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100378800","display_name":"Tong Zhang","orcid":"https://orcid.org/0000-0002-7025-6365"},"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":"Tong Zhang","raw_affiliation_strings":["State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Hubei, China","[State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China]"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I4210118728","https://openalex.org/I37461747"]},{"raw_affiliation_string":"[State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China]","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100391116","display_name":"Qian Wang","orcid":"https://orcid.org/0000-0002-8967-8525"},"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":"Qian Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University, Hubei, China","School of Computer Science, Wuhan University Wuhan China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Hubei, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University Wuhan China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5070093927"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":47.115,"has_fulltext":false,"cited_by_count":924,"citation_normalized_percentile":{"value":0.99884925,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"12","issue":"11","first_page":"2321","last_page":"2325"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"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":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9962000250816345,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9926999807357788,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7892987132072449},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7802953124046326},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6599269509315491},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6420286297798157},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6140206456184387},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5932576656341553},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5836337804794312},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5420566201210022},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4856351912021637},{"id":"https://openalex.org/keywords/intrinsics","display_name":"Intrinsics","score":0.4440310001373291},{"id":"https://openalex.org/keywords/deep-belief-network","display_name":"Deep belief network","score":0.43391329050064087},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37611323595046997}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7892987132072449},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7802953124046326},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6599269509315491},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6420286297798157},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6140206456184387},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5932576656341553},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5836337804794312},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5420566201210022},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4856351912021637},{"id":"https://openalex.org/C2908650547","wikidata":"https://www.wikidata.org/wiki/Q20999234","display_name":"Intrinsics","level":2,"score":0.4440310001373291},{"id":"https://openalex.org/C97385483","wikidata":"https://www.wikidata.org/wiki/Q16954980","display_name":"Deep belief network","level":3,"score":0.43391329050064087},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37611323595046997},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2015.2475299","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2475299","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":[{"score":0.7200000286102295,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G1428221054","display_name":null,"funder_award_id":"61301277","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4741835796","display_name":null,"funder_award_id":"41371431","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4929584277","display_name":null,"funder_award_id":"2012CB725303","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6732584608","display_name":null,"funder_award_id":"2012CB719906","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program 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/F4320324116","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17"},{"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":23,"referenced_works":["https://openalex.org/W2015420370","https://openalex.org/W2029949252","https://openalex.org/W2030353835","https://openalex.org/W2091280333","https://openalex.org/W2100495367","https://openalex.org/W2101927381","https://openalex.org/W2102927912","https://openalex.org/W2103564202","https://openalex.org/W2110798204","https://openalex.org/W2136922672","https://openalex.org/W2143130611","https://openalex.org/W2150341604","https://openalex.org/W2154506590","https://openalex.org/W2163605009","https://openalex.org/W2169042894","https://openalex.org/W2172174689","https://openalex.org/W2332646948","https://openalex.org/W2618530766","https://openalex.org/W4205947740","https://openalex.org/W4300402905","https://openalex.org/W6676481782","https://openalex.org/W6684191040","https://openalex.org/W6684753728"],"related_works":["https://openalex.org/W2594876342","https://openalex.org/W3127162800","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353","https://openalex.org/W3003646942","https://openalex.org/W3036573187"],"abstract_inverted_index":{"With":[0],"the":[1,30,45,55,60,70,74,93,103,114,118,123,141,144],"popular":[2,56],"use":[3],"of":[4,130,143],"high-resolution":[5],"satellite":[6],"images,":[7],"more":[8,10,86,100],"and":[9,78],"research":[11],"efforts":[12],"have":[13],"been":[14],"placed":[15],"on":[16],"remote":[17,126],"sensing":[18,127],"scene":[19,22,128],"classification/recognition.":[20],"In":[21,33,122],"classification,":[23],"effective":[24],"feature":[25,50,66,76,87],"selection":[26],"can":[27],"significantly":[28],"boost":[29],"final":[31],"performance.":[32],"this":[34],"letter,":[35],"a":[36,49],"novel":[37],"deep-learning-based":[38],"feature-selection":[39,46],"method":[40,95],"is":[41,110],"proposed,":[42],"which":[43],"formulates":[44],"problem":[47],"as":[48,102],"reconstruction":[51,71,82,120],"problem.":[52],"Note":[53],"that":[54,98],"deep-learning":[57],"technique,":[58],"i.e.,":[59],"deep":[61],"belief":[62],"network":[63],"(DBN),":[64],"achieves":[65],"abstraction":[67],"by":[68],"minimizing":[69],"error":[72],"over":[73],"whole":[75],"set,":[77],"features":[79,97],"with":[80],"smaller":[81],"errors":[83],"would":[84],"hold":[85],"intrinsics":[88],"for":[89,135],"image":[90],"representation.":[91],"Therefore,":[92],"proposed":[94,145],"selects":[96],"are":[99,133],"reconstructible":[101],"discriminative":[104],"features.":[105],"Specifically,":[106],"an":[107],"iterative":[108],"algorithm":[109],"developed":[111],"to":[112,116],"adapt":[113],"DBN":[115],"produce":[117],"inquired":[119],"weights.":[121],"experiments,":[124],"2800":[125],"images":[129],"seven":[131],"categories":[132],"collected":[134],"performance":[136],"evaluation.":[137],"Experimental":[138],"results":[139],"demonstrate":[140],"effectiveness":[142],"method.":[146]},"counts_by_year":[{"year":2026,"cited_by_count":24},{"year":2025,"cited_by_count":125},{"year":2024,"cited_by_count":104},{"year":2023,"cited_by_count":110},{"year":2022,"cited_by_count":94},{"year":2021,"cited_by_count":135},{"year":2020,"cited_by_count":104},{"year":2019,"cited_by_count":116},{"year":2018,"cited_by_count":56},{"year":2017,"cited_by_count":40},{"year":2016,"cited_by_count":16}],"updated_date":"2026-04-12T07:58:50.170612","created_date":"2025-10-10T00:00:00"}