{"id":"https://openalex.org/W2168534096","doi":"https://doi.org/10.1109/lgrs.2015.2408433","title":"Real-Time Implementation of the Sparse Multinomial Logistic Regression for Hyperspectral Image Classification on GPUs","display_name":"Real-Time Implementation of the Sparse Multinomial Logistic Regression for Hyperspectral Image Classification on GPUs","publication_year":2015,"publication_date":"2015-03-18","ids":{"openalex":"https://openalex.org/W2168534096","doi":"https://doi.org/10.1109/lgrs.2015.2408433","mag":"2168534096"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2015.2408433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2408433","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/A5031361250","display_name":"Zebin Wu","orcid":"https://orcid.org/0000-0002-7162-0202"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zebin Wu","raw_affiliation_strings":["Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090796235","display_name":"Qicong Wang","orcid":"https://orcid.org/0000-0001-7324-0433"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qicong Wang","raw_affiliation_strings":["Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Dept. of Technol. of Comput. & Commun., Univ. of Extremadura, Caceres, Spain"],"affiliations":[{"raw_affiliation_string":"Dept. of Technol. of Comput. & Commun., Univ. of Extremadura, Caceres, Spain","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100362041","display_name":"Jun Li","orcid":"https://orcid.org/0000-0003-1613-9448"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Li","raw_affiliation_strings":["Guangdong Provincial Key Lab. of Urbanization & Geo-simulation, Sun Yat-sen Univ., Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Provincial Key Lab. of Urbanization & Geo-simulation, Sun Yat-sen Univ., Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059068224","display_name":"Le Sun","orcid":"https://orcid.org/0000-0001-6465-8678"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Le Sun","raw_affiliation_strings":["Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101005533","display_name":"Zhihui Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Wei","raw_affiliation_strings":["Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Sch. of Comput. Sci. & Eng., Nanjing Univ. of Sci. & Technol., Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5031361250"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":7.5721,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.97326147,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"12","issue":"7","first_page":"1456","last_page":"1460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9901000261306763,"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":0.9825000166893005,"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/computer-science","display_name":"Computer science","score":0.7812807559967041},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.683176577091217},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.6676053404808044},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.6003984212875366},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5553845763206482},{"id":"https://openalex.org/keywords/cuda","display_name":"CUDA","score":0.5159867405891418},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5051971077919006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4439622461795807},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.43497079610824585},{"id":"https://openalex.org/keywords/multinomial-distribution","display_name":"Multinomial distribution","score":0.43274638056755066},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.4285484254360199},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4114598035812378},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3015373647212982},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11539331078529358},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11137819290161133},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.10003113746643066}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7812807559967041},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.683176577091217},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.6676053404808044},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.6003984212875366},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5553845763206482},{"id":"https://openalex.org/C2778119891","wikidata":"https://www.wikidata.org/wiki/Q477690","display_name":"CUDA","level":2,"score":0.5159867405891418},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5051971077919006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4439622461795807},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.43497079610824585},{"id":"https://openalex.org/C192065140","wikidata":"https://www.wikidata.org/wiki/Q1147928","display_name":"Multinomial distribution","level":2,"score":0.43274638056755066},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.4285484254360199},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4114598035812378},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3015373647212982},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11539331078529358},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11137819290161133},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.10003113746643066},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2015.2408433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2015.2408433","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":[],"awards":[{"id":"https://openalex.org/G162465282","display_name":null,"funder_award_id":"61 101194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G235825336","display_name":null,"funder_award_id":"20113219120024","funder_id":"https://openalex.org/F4320336024","funder_display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China"},{"id":"https://openalex.org/G5049696438","display_name":null,"funder_award_id":"61471199","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6224043322","display_name":null,"funder_award_id":"CAST201227","funder_id":"https://openalex.org/F4320334995","funder_display_name":"CAST Innovation Foundation"},{"id":"https://openalex.org/G6724906057","display_name":null,"funder_award_id":"201406845012","funder_id":"https://openalex.org/F4320331311","funder_display_name":"China Oxford Scholarship Fund"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320331311","display_name":"China Oxford Scholarship Fund","ror":null},{"id":"https://openalex.org/F4320334995","display_name":"CAST Innovation Foundation","ror":null},{"id":"https://openalex.org/F4320336024","display_name":"Specialized Research Fund for the Doctoral Program of Higher Education of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1979730959","https://openalex.org/W2001298023","https://openalex.org/W2006690683","https://openalex.org/W2009286595","https://openalex.org/W2048056733","https://openalex.org/W2077239519","https://openalex.org/W2131697388","https://openalex.org/W2136251662","https://openalex.org/W2150579376","https://openalex.org/W2154970996","https://openalex.org/W2156454229","https://openalex.org/W2167256583"],"related_works":["https://openalex.org/W4399354997","https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2404757046","https://openalex.org/W3098841390","https://openalex.org/W2784774275","https://openalex.org/W1917858188"],"abstract_inverted_index":{"In":[0],"this":[1],"letter,":[2],"a":[3],"real-time":[4,66,89],"implementation":[5],"of":[6,58,62,69,106],"the":[7,43,47,59,73,77,94,101,107],"logistic":[8,21],"regression":[9,22],"via":[10],"variable":[11],"splitting":[12],"and":[13,54,88,103],"augmented":[14],"Lagrangian":[15],"(LORSAL)":[16],"algorithm":[17],"for":[18,72],"sparse":[19],"multinomial":[20],"is":[23],"presented":[24],"on":[25],"commodity":[26],"graphics":[27],"processing":[28],"units":[29],"(GPUs)":[30],"using":[31],"Nvidia's":[32],"compute":[33],"unified":[34],"device":[35],"architecture.":[36],"The":[37],"proposed":[38],"parallel":[39],"method":[40],"properly":[41],"exploits":[42],"GPU":[44],"architecture":[45],"at":[46],"low":[48],"level,":[49],"including":[50],"its":[51],"shared":[52],"memory,":[53],"takes":[55],"full":[56],"advantage":[57],"computational":[60],"power":[61],"GPUs":[63],"to":[64,100],"achieve":[65],"classification":[67,96],"performance":[68],"hyperspectral":[70,78],"images":[71],"first":[74],"time":[75],"in":[76],"imaging":[79],"literature.":[80],"Our":[81],"experimental":[82],"results":[83],"reveal":[84],"remarkable":[85],"acceleration":[86],"factors":[87],"performance,":[90],"while":[91],"retaining":[92],"exactly":[93],"same":[95],"accuracy":[97],"with":[98],"regard":[99],"serial":[102],"multicore":[104],"versions":[105],"classifier.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}