{"id":"https://openalex.org/W4391942813","doi":"https://doi.org/10.1109/whispers61460.2023.10430920","title":"Spectral-Spatial Hyperspectral Unmixing Using Double-Constraints Convolutional Autoencoder","display_name":"Spectral-Spatial Hyperspectral Unmixing Using Double-Constraints Convolutional Autoencoder","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4391942813","doi":"https://doi.org/10.1109/whispers61460.2023.10430920"},"language":"en","primary_location":{"id":"doi:10.1109/whispers61460.2023.10430920","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/whispers61460.2023.10430920","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-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/A5101574132","display_name":"Zhiqing Zhu","orcid":"https://orcid.org/0009-0006-6606-8640"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqing Zhu","raw_affiliation_strings":["Xi&#x2019;an University of Science and Technology,College of Geomatics,Xi&#x2019;an,China,710054"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Science and Technology,College of Geomatics,Xi&#x2019;an,China,710054","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087502613","display_name":"Yuanchao Su","orcid":"https://orcid.org/0000-0002-4776-0862"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanchao Su","raw_affiliation_strings":["Xi&#x2019;an University of Science and Technology,College of Geomatics,Xi&#x2019;an,China,710054"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Science and Technology,College of Geomatics,Xi&#x2019;an,China,710054","institution_ids":["https://openalex.org/I110440473"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023324327","display_name":"Mengying Jiang","orcid":"https://orcid.org/0000-0001-6650-1818"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengying Jiang","raw_affiliation_strings":["Xi&#x2019;an Jiaotong University,School of Electronics and Information Engineering,Xi&#x2019;an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Jiaotong University,School of Electronics and Information Engineering,Xi&#x2019;an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049136910","display_name":"Bin Pan","orcid":"https://orcid.org/0000-0003-3063-1762"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Pan","raw_affiliation_strings":["Nankai University,School of Statistics and Data Science,Tianjin,China,300071"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nankai University,School of Statistics and Data Science,Tianjin,China,300071","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101306686","display_name":"Jinying Bai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jinying Bai","raw_affiliation_strings":["Xi&#x2019;an Piesat Information Technology Co., Ltd.,Xi&#x2019;an,China,710100"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an Piesat Information Technology Co., Ltd.,Xi&#x2019;an,China,710100","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100339773","display_name":"Pengfei Li","orcid":"https://orcid.org/0000-0003-1173-5654"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Li","raw_affiliation_strings":["Xi&#x2019;an University of Science and Technology,College of Geomatics,Xi&#x2019;an,China,710054"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi&#x2019;an University of Science and Technology,College of Geomatics,Xi&#x2019;an,China,710054","institution_ids":["https://openalex.org/I110440473"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.28469888,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"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":0.9965999722480774,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.9016373753547668},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8908818364143372},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6547445058822632},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5473166108131409},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5184416770935059},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4880908727645874},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3614481985569},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1788100302219391},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12795665860176086}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9016373753547668},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8908818364143372},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6547445058822632},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5473166108131409},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5184416770935059},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4880908727645874},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3614481985569},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1788100302219391},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12795665860176086}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers61460.2023.10430920","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/whispers61460.2023.10430920","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 13th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1963659868","https://openalex.org/W1983364832","https://openalex.org/W2037328426","https://openalex.org/W2087263574","https://openalex.org/W2127062304","https://openalex.org/W2163886442","https://openalex.org/W2755992512","https://openalex.org/W2760901445","https://openalex.org/W2894115892","https://openalex.org/W2911419410","https://openalex.org/W3005148902","https://openalex.org/W3028000844","https://openalex.org/W3106244377","https://openalex.org/W3110749113","https://openalex.org/W3137191419","https://openalex.org/W3158091052","https://openalex.org/W3205148564","https://openalex.org/W4205095826","https://openalex.org/W4285223668","https://openalex.org/W4285269366","https://openalex.org/W4309367935"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W2159052453","https://openalex.org/W2072166414","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190"],"abstract_inverted_index":{"Recently,":[0],"the":[1,34,39,47,51,71,76,84,87,104,108,117,121,124,136,151],"development":[2],"of":[3,29,50,86,120,155],"deep":[4],"learning":[5],"(DL)":[6],"opens":[7],"a":[8,61,114],"new":[9,109],"path":[10],"for":[11],"achieving":[12],"hyperspectral":[13,80],"unmixing.":[14],"The":[15,66],"DL-based":[16],"unmixing":[17,25],"methods":[18,31],"show":[19],"many":[20],"advantages":[21],"compared":[22],"with":[23,56,147],"traditional":[24],"methods.":[26],"However,":[27],"most":[28],"these":[30],"only":[32],"consider":[33],"spectral":[35,94],"information":[36,78],"and":[37,153],"ignore":[38],"spatial":[40],"distribution,":[41],"which":[42],"might":[43],"lead":[44],"to":[45,46,74,139],"poor":[48],"smoothness":[49],"estimated":[52],"abundance.":[53],"To":[54],"deal":[55],"this":[57,100],"problem,":[58],"we":[59,112,129],"proposed":[60,68],"double-constraints":[62],"convolution":[63],"autoencoder":[64],"(DCAE).":[65],"newly":[67],"method":[69],"uses":[70],"convolutional":[72],"network":[73,110],"capture":[75],"spectral-spatial":[77],"from":[79],"data.":[81],"By":[82],"utilizing":[83],"output":[85],"Gaussian":[88],"function":[89,119],"can":[90,102],"distinguish":[91],"between":[92],"two":[93],"similar":[95],"but":[96],"different":[97],"materials.":[98],"Meanwhile,":[99],"strategy":[101],"improve":[103],"abundance":[105,125],"smoothness.":[106],"In":[107,127],"structure,":[111],"adopt":[113],"softmax":[115,137],"as":[116],"activation":[118],"abundances":[122],"constrain":[123],"estimation.":[126],"addition,":[128],"add":[130],"L<inf":[131],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[132],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1/2</inf>":[133],"regularization":[134],"in":[135],"layer":[138],"avoid":[140],"overfitting":[141],"when":[142],"completing":[143],"nodes":[144],"embedding(NE).":[145],"Experiments":[146],"real":[148],"datasets":[149],"verify":[150],"effectiveness":[152],"competitiveness":[154],"our":[156],"DCAE.":[157]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}