{"id":"https://openalex.org/W2940678725","doi":"https://doi.org/10.1109/tgrs.2019.2908756","title":"Unsupervised Spatial\u2013Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification","display_name":"Unsupervised Spatial\u2013Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification","publication_year":2019,"publication_date":"2019-04-25","ids":{"openalex":"https://openalex.org/W2940678725","doi":"https://doi.org/10.1109/tgrs.2019.2908756","mag":"2940678725"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2019.2908756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2908756","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/A5067207818","display_name":"Shaohui Mei","orcid":"https://orcid.org/0000-0002-8018-596X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaohui Mei","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022330186","display_name":"Jingyu Ji","orcid":"https://orcid.org/0000-0001-6806-7437"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Ji","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062767075","display_name":"Yunhao Geng","orcid":"https://orcid.org/0000-0003-0120-6679"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhao Geng","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100749618","display_name":"Zhi Zhang","orcid":"https://orcid.org/0009-0000-5180-0452"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]},{"id":"https://openalex.org/I4210166112","display_name":"State Key Laboratory of Remote Sensing Science","ror":"https://ror.org/05wzjqa24","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210166112"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zhang","raw_affiliation_strings":["State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210166112","https://openalex.org/I4210128053","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100648032","display_name":"Li Xu","orcid":"https://orcid.org/0000-0002-4497-3280"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Li","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi\u2019an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033017179","display_name":"Qian Du","orcid":"https://orcid.org/0000-0001-8354-7500"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Du","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Geosystems Research Institute, Mississippi State University, Starkville, MS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Geosystems Research Institute, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5067207818"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":26.6063,"has_fulltext":false,"cited_by_count":307,"citation_normalized_percentile":{"value":0.99726838,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"57","issue":"9","first_page":"6808","last_page":"6820"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"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":0.991100013256073,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7871202230453491},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7585395574569702},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7563774585723877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7269771099090576},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6985021829605103},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6850301623344421},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6425726413726807},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5223007202148438},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4956594705581665},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.48384395241737366},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.451956182718277},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.424238920211792}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7871202230453491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7585395574569702},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7563774585723877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7269771099090576},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6985021829605103},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6850301623344421},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6425726413726807},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5223007202148438},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4956594705581665},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.48384395241737366},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.451956182718277},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.424238920211792},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2019.2908756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2019.2908756","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/G470046289","display_name":null,"funder_award_id":"3102018AX001","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4801475360","display_name":null,"funder_award_id":"61671383","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5208857031","display_name":null,"funder_award_id":"2018JM6005","funder_id":"https://openalex.org/F4320324173","funder_display_name":"Natural Science Foundation of Shaanxi Province"},{"id":"https://openalex.org/G7384725169","display_name":null,"funder_award_id":"2014M550872","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"},{"id":"https://openalex.org/G7815016644","display_name":null,"funder_award_id":"61301235","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/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320324173","display_name":"Natural Science Foundation of Shaanxi Province","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W625476304","https://openalex.org/W639708223","https://openalex.org/W1521436688","https://openalex.org/W1522734439","https://openalex.org/W1677182931","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W1924619199","https://openalex.org/W1966580635","https://openalex.org/W1967810897","https://openalex.org/W1976359033","https://openalex.org/W1983364832","https://openalex.org/W1990895816","https://openalex.org/W2029316659","https://openalex.org/W2037328426","https://openalex.org/W2041785029","https://openalex.org/W2077776048","https://openalex.org/W2090826137","https://openalex.org/W2097117768","https://openalex.org/W2102605133","https://openalex.org/W2103250033","https://openalex.org/W2106777458","https://openalex.org/W2114528672","https://openalex.org/W2118796925","https://openalex.org/W2129149445","https://openalex.org/W2134740107","https://openalex.org/W2150341604","https://openalex.org/W2151599207","https://openalex.org/W2153635508","https://openalex.org/W2154536501","https://openalex.org/W2154872931","https://openalex.org/W2156718197","https://openalex.org/W2162698522","https://openalex.org/W2163605009","https://openalex.org/W2163922914","https://openalex.org/W2165573608","https://openalex.org/W2167685974","https://openalex.org/W2171171329","https://openalex.org/W2179290474","https://openalex.org/W2194775991","https://openalex.org/W2314785379","https://openalex.org/W2324845311","https://openalex.org/W2331181944","https://openalex.org/W2342877626","https://openalex.org/W2345128667","https://openalex.org/W2517189067","https://openalex.org/W2548791488","https://openalex.org/W2597644092","https://openalex.org/W2602031553","https://openalex.org/W2611655888","https://openalex.org/W2625436554","https://openalex.org/W2767805377","https://openalex.org/W2768537477","https://openalex.org/W2775464024","https://openalex.org/W2799390666","https://openalex.org/W2949117887","https://openalex.org/W2949608135","https://openalex.org/W2963420272","https://openalex.org/W2963920537","https://openalex.org/W4205947740","https://openalex.org/W6675955514","https://openalex.org/W6682644385","https://openalex.org/W6682755970","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W4220682630","https://openalex.org/W4389832810","https://openalex.org/W3181622257","https://openalex.org/W3163146846"],"abstract_inverted_index":{"Feature":[0],"learning":[1,56],"technologies":[2],"using":[3,63],"convolutional":[4,66,101],"neural":[5],"networks":[6],"(CNNs)":[7],"have":[8,159],"shown":[9],"superior":[10],"performance":[11],"over":[12],"traditional":[13,176],"hand-crafted":[14],"feature":[15,55,96,178,185],"extraction":[16,179,186],"algorithms.":[17],"However,":[18],"a":[19,133],"large":[20],"number":[21],"of":[22,73,146],"labeled":[23,129],"samples":[24],"are":[25,38,137],"generally":[26],"required":[27],"for":[28,43,60,95],"CNN":[29],"to":[30,40,89,107,112],"learn":[31],"effective":[32,135,167],"features":[33,136,171],"under":[34],"classification":[35,189],"task,":[36],"which":[37,117],"hard":[39],"be":[41,126],"obtained":[42],"hyperspectral":[44,61,156],"remote":[45],"sensing":[46],"images.":[47],"Therefore,":[48],"in":[49,122,139,168,188],"this":[50],"paper,":[51],"an":[52,140],"unsupervised":[53,141,177],"spatial-spectral":[54,92,170],"strategy":[57],"is":[58,104,148,165],"proposed":[59,70,114,163],"images":[62],"3-Dimensional":[64],"(3D)":[65],"autoencoder":[67],"(3D-CAE).":[68],"The":[69],"3D-CAE":[71,164],"consists":[72],"3D":[74,81,83,86,100],"or":[75],"elementwise":[76],"operations":[77],"only,":[78],"such":[79],"as":[80],"convolution,":[82],"pooling,":[84],"and":[85,172],"batch":[87],"normalization,":[88],"maximally":[90],"explore":[91],"structure":[93],"information":[94,145],"extraction.":[97],"A":[98],"companion":[99],"decoder":[102],"network":[103,124],"also":[105,182],"designed":[106],"reconstruct":[108],"the":[109,113,119,123],"input":[110],"patterns":[111],"3D-CAE,":[115],"by":[116],"all":[118],"parameters":[120],"involved":[121],"can":[125],"trained":[127],"without":[128],"training":[130],"samples.":[131],"As":[132],"result,":[134],"learned":[138],"mode":[142],"that":[143,161],"label":[144],"pixels":[147],"not":[149,174],"required.":[150],"Experimental":[151],"results":[152],"on":[153],"several":[154],"benchmark":[155],"data":[157],"sets":[158],"demonstrated":[160],"our":[162],"very":[166],"extracting":[169],"outperforms":[173],"only":[175],"algorithms":[180,187],"but":[181],"many":[183],"supervised":[184],"application.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":31},{"year":2024,"cited_by_count":60},{"year":2023,"cited_by_count":67},{"year":2022,"cited_by_count":63},{"year":2021,"cited_by_count":58},{"year":2020,"cited_by_count":22},{"year":2019,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}