{"id":"https://openalex.org/W3024039333","doi":"https://doi.org/10.1109/lgrs.2020.2989796","title":"Hapke Data Augmentation for Deep Learning-Based Hyperspectral Data Analysis With Limited Samples","display_name":"Hapke Data Augmentation for Deep Learning-Based Hyperspectral Data Analysis With Limited Samples","publication_year":2020,"publication_date":"2020-05-15","ids":{"openalex":"https://openalex.org/W3024039333","doi":"https://doi.org/10.1109/lgrs.2020.2989796","mag":"3024039333"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2020.2989796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.2989796","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/A5101766471","display_name":"Kai Qin","orcid":"https://orcid.org/0000-0002-1280-6330"},"institutions":[{"id":"https://openalex.org/I4210134214","display_name":"Beijing Research Institute of Uranium Geology","ror":"https://ror.org/046qx3a23","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210134214"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Qin","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China","institution_ids":["https://openalex.org/I4210134214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085790208","display_name":"Fangyuan Ge","orcid":null},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangyuan Ge","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100930552","display_name":"Yingjun Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134214","display_name":"Beijing Research Institute of Uranium Geology","ror":"https://ror.org/046qx3a23","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210134214"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjun Zhao","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China","institution_ids":["https://openalex.org/I4210134214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101475200","display_name":"Ling Zhu","orcid":"https://orcid.org/0000-0003-3406-8401"},"institutions":[{"id":"https://openalex.org/I4210134214","display_name":"Beijing Research Institute of Uranium Geology","ror":"https://ror.org/046qx3a23","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210134214"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Zhu","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China","institution_ids":["https://openalex.org/I4210134214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351539","display_name":"Ming Li","orcid":"https://orcid.org/0000-0003-4781-9489"},"institutions":[{"id":"https://openalex.org/I4210134214","display_name":"Beijing Research Institute of Uranium Geology","ror":"https://ror.org/046qx3a23","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210134214"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4781-9489","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Science and Technology on Remote Sensing Information and Image Analysis, National Nuclear Corp, Beijing Research Institute of Uranium Geology, Beijing, China","institution_ids":["https://openalex.org/I4210134214"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069699411","display_name":"Cong Shi","orcid":"https://orcid.org/0000-0003-0040-4411"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cong Shi","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-0040-4411","affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100407536","display_name":"Dong Li","orcid":"https://orcid.org/0000-0003-4766-3808"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Li","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-4766-3808","affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010601964","display_name":"Xichuan Zhou","orcid":"https://orcid.org/0000-0002-3304-3045"},"institutions":[{"id":"https://openalex.org/I158842170","display_name":"Chongqing University","ror":"https://ror.org/023rhb549","country_code":"CN","type":"education","lineage":["https://openalex.org/I158842170"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xichuan Zhou","raw_affiliation_strings":["School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-3304-3045","affiliations":[{"raw_affiliation_string":"School of Microelectronics and Communication Engineering, Chongqing University, Chongqing, China","institution_ids":["https://openalex.org/I158842170"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0799,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.89693961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"18","issue":"5","first_page":"886","last_page":"890"},"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/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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9872999787330627,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9588158130645752},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7026519775390625},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6347715258598328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6165452003479004},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5735491514205933},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5723528265953064},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.5650435090065002},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4443749785423279},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4123436510562897},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4110787808895111},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.1819455325603485}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9588158130645752},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7026519775390625},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6347715258598328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6165452003479004},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5735491514205933},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5723528265953064},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.5650435090065002},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4443749785423279},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4123436510562897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4110787808895111},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.1819455325603485},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2020.2989796","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2020.2989796","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":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5899999737739563}],"awards":[{"id":"https://openalex.org/G6290650912","display_name":null,"funder_award_id":"41602333","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8673984432","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u56fe\u50cf\u5f31\u76d1\u7763\u6df1\u5ea6\u5b66\u4e60\u7406\u8bba\u4e0e\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61971072","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1836465849","https://openalex.org/W1976615758","https://openalex.org/W2053762059","https://openalex.org/W2078222544","https://openalex.org/W2084252873","https://openalex.org/W2101837437","https://openalex.org/W2127062304","https://openalex.org/W2157321686","https://openalex.org/W2500751094","https://openalex.org/W2560523472","https://openalex.org/W2770697776","https://openalex.org/W2775795276","https://openalex.org/W2797175432","https://openalex.org/W2886042776","https://openalex.org/W2901076994","https://openalex.org/W2949117887","https://openalex.org/W2963371848","https://openalex.org/W6638667902","https://openalex.org/W6745747308","https://openalex.org/W6747218270"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W4377865163","https://openalex.org/W3193857078","https://openalex.org/W2888956734","https://openalex.org/W4315865067","https://openalex.org/W2979433843","https://openalex.org/W3208304128","https://openalex.org/W3000197790"],"abstract_inverted_index":{"The":[0],"emerging":[1],"technology":[2],"of":[3,43,80],"deep":[4,27,37],"neural":[5,38],"networks":[6,39],"has":[7],"been":[8],"proven":[9],"to":[10,24],"be":[11,55],"successful":[12],"for":[13,30,46,59,109],"hyperspectral":[14,81,95],"image":[15],"analysis.":[16,112],"However,":[17],"it":[18],"is":[19],"still":[20],"a":[21,50,71],"great":[22],"challenge":[23],"apply":[25],"the":[26,78,85,101,105],"learning":[28],"method":[29,103],"quantitatively":[31],"retrieving":[32],"mineralogical":[33],"composition,":[34],"because":[35],"typical":[36],"generally":[40],"require":[41],"thousands":[42],"labeled":[44],"samples":[45,53],"training,":[47],"while":[48],"only":[49],"few":[51],"mineral":[52,111],"can":[54],"acquired":[56],"and":[57,93],"examined":[58],"quantitative":[60,110],"examination":[61],"in":[62],"practice.":[63],"To":[64],"address":[65],"this":[66,68],"challenge,":[67],"letter":[69],"proposes":[70],"training":[72],"data":[73,98],"augmentation":[74],"approach":[75],"which":[76],"incorporates":[77],"prior-knowledge":[79],"reflectance":[82],"characteristics":[83],"using":[84],"classic":[86],"Hapke":[87],"equations.":[88],"Experiments":[89],"over":[90],"both":[91],"laboratory":[92],"airborne":[94],"remote":[96],"sensing":[97],"show":[99],"that":[100],"proposed":[102],"outperforms":[104],"widely":[106],"used":[107],"approaches":[108]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
