{"id":"https://openalex.org/W4391923799","doi":"https://doi.org/10.1109/whispers61460.2023.10431010","title":"Endmember Variable Mineral Mapping with Bayesian Convolutional Unmixing Network Using Prisma Hyperspectral Imagery","display_name":"Endmember Variable Mineral Mapping with Bayesian Convolutional Unmixing Network Using Prisma Hyperspectral Imagery","publication_year":2023,"publication_date":"2023-10-31","ids":{"openalex":"https://openalex.org/W4391923799","doi":"https://doi.org/10.1109/whispers61460.2023.10431010"},"language":"en","primary_location":{"id":"doi:10.1109/whispers61460.2023.10431010","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/whispers61460.2023.10431010","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":"conference-paper","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/A5079218325","display_name":"Yuan Fang","orcid":"https://orcid.org/0000-0001-5740-9526"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yuan Fang","raw_affiliation_strings":["University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035521353","display_name":"Alexander De Souza","orcid":"https://orcid.org/0000-0002-1158-3219"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alexander De Souza","raw_affiliation_strings":["Skywatch,Kitchener,ON,Canada,N2H 2G8"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Skywatch,Kitchener,ON,Canada,N2H 2G8","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034166335","display_name":"Linlin Xu","orcid":"https://orcid.org/0000-0002-3488-5199"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Linlin Xu","raw_affiliation_strings":["University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100682003","display_name":"Xinwei Chen","orcid":"https://orcid.org/0000-0003-0649-7284"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Xinwei Chen","raw_affiliation_strings":["University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066149942","display_name":"David A. Clausi","orcid":"https://orcid.org/0000-0002-6383-0875"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"David A. Clausi","raw_affiliation_strings":["University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Waterloo,Dept. of Systems Design Engineering,Waterloo,ON,Canada,N2L 3G1","institution_ids":["https://openalex.org/I151746483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9994999766349792,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.9994999766349792,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9991999864578247,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9735999703407288,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/endmember","display_name":"Endmember","score":0.9789096117019653},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9243466258049011},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.630909264087677},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.623062252998352},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.518494725227356},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4892711341381073},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4357847571372986},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4026497006416321},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.24920165538787842},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18283197283744812}],"concepts":[{"id":"https://openalex.org/C58237817","wikidata":"https://www.wikidata.org/wiki/Q5376204","display_name":"Endmember","level":3,"score":0.9789096117019653},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9243466258049011},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.630909264087677},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.623062252998352},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.518494725227356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4892711341381073},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4357847571372986},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4026497006416321},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.24920165538787842},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18283197283744812},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/whispers61460.2023.10431010","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/whispers61460.2023.10431010","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":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/13","display_name":"Climate action"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W194868758","https://openalex.org/W1629102637","https://openalex.org/W2157321686","https://openalex.org/W2261059368","https://openalex.org/W2330747182","https://openalex.org/W2342603028","https://openalex.org/W2346349995","https://openalex.org/W2500751094","https://openalex.org/W2782865993","https://openalex.org/W2962832489","https://openalex.org/W2985950345","https://openalex.org/W3094336554","https://openalex.org/W4210987640","https://openalex.org/W4312085175"],"related_works":["https://openalex.org/W2037328426","https://openalex.org/W1990914742","https://openalex.org/W2891033441","https://openalex.org/W2006559622","https://openalex.org/W3106536224","https://openalex.org/W2890371384","https://openalex.org/W2051769241","https://openalex.org/W2563324120","https://openalex.org/W2040756827","https://openalex.org/W3045038000"],"abstract_inverted_index":{"Mineral":[0],"mapping":[1,38],"identifies":[2],"minerals":[3],"distributed":[4],"in":[5,15],"a":[6,12,33,46],"specific":[7],"geographic":[8],"area":[9],"and":[10,18,27,61,76,87,101],"plays":[11],"significant":[13],"role":[14],"several":[16],"fields":[17],"industries,":[19],"such":[20],"as":[21],"mining,":[22],"environmental":[23],"monitoring,":[24],"land":[25],"management,":[26],"space":[28],"exploration.":[29],"Hyperspectral":[30],"imaging":[31],"is":[32],"fast-developing":[34],"technique":[35],"for":[36],"mineral":[37,65],"due":[39],"to":[40,59],"its":[41],"outstanding":[42],"discriminating":[43],"ability":[44],"with":[45,52],"wide":[47],"range":[48],"of":[49],"spectral":[50,54,103],"bands":[51],"high":[53],"resolution.":[55],"This":[56],"paper":[57],"aims":[58],"effectively":[60],"accurately":[62],"map":[63],"the":[64,71,84],"distribution":[66],"at":[67],"Cuprite,":[68],"Nevada":[69],"using":[70],"new":[72],"Prisma":[73],"hyperspectral":[74],"imagery":[75],"novel":[77],"Bayesian":[78],"convolutional":[79],"unmixing":[80,104],"network":[81],"algorithm":[82],"modeling":[83],"endmember":[85],"variability":[86],"spatial":[88],"correlation.":[89],"Comparative":[90],"results":[91],"show":[92],"that":[93],"our":[94],"proposed":[95],"method":[96],"outperforms":[97],"both":[98],"classification-based":[99],"algorithms":[100],"traditional":[102],"approach":[105],"given":[106],"limited":[107],"training":[108],"samples.":[109]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
