{"id":"https://openalex.org/W2087354971","doi":"https://doi.org/10.1109/igarss.2013.6721336","title":"Supervised hyperspectral image classification using sparse logistic regression and spatial-TV regularization","display_name":"Supervised hyperspectral image classification using sparse logistic regression and spatial-TV regularization","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W2087354971","doi":"https://doi.org/10.1109/igarss.2013.6721336","mag":"2087354971"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2013.6721336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2013.6721336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS","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/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":["NJUST, School of Computer Science, Nanjing, P. R. China","Sch. of Comput. Sci., NJUST, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NJUST, School of Computer Science, Nanjing, P. R. China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Sch. of Comput. Sci., NJUST, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045937069","display_name":"Zenbin Wu","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":"Zenbin Wu","raw_affiliation_strings":["NJUST, Jiangsu Key Lab of Spectral Imaging and Intelligent Sensing, P. R. China","Sch. of Comput. Sci., NJUST, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NJUST, Jiangsu Key Lab of Spectral Imaging and Intelligent Sensing, P. R. China","institution_ids":[]},{"raw_affiliation_string":"Sch. of Comput. Sci., NJUST, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026335073","display_name":"Jianjun Liu","orcid":"https://orcid.org/0000-0002-9520-2443"},"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":"Jianjun Liu","raw_affiliation_strings":["NJUST, School of Computer Science, Nanjing, P. R. China","Sch. of Comput. Sci., NJUST, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NJUST, School of Computer Science, Nanjing, P. R. China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Sch. of Comput. Sci., NJUST, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070343691","display_name":"Zhihui Wei","orcid":"https://orcid.org/0000-0002-4841-6051"},"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":["NJUST, School of Computer Science, Nanjing, P. R. China","Sch. of Comput. Sci., NJUST, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NJUST, School of Computer Science, Nanjing, P. R. China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Sch. of Comput. Sci., NJUST, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":4.3593,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.95884004,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"19","issue":null,"first_page":"1019","last_page":"1022"},"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":0.9855999946594238,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9053999781608582,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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":0.9058728814125061},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6530464887619019},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.6248015761375427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6233370304107666},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6201061606407166},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5961170196533203},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4837517738342285},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.47858572006225586},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.45439696311950684},{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.4253268837928772},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34453755617141724},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.342966228723526},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29190492630004883},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.21294018626213074},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19932234287261963}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9058728814125061},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6530464887619019},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.6248015761375427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6233370304107666},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6201061606407166},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5961170196533203},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4837517738342285},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.47858572006225586},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.45439696311950684},{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.4253268837928772},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34453755617141724},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.342966228723526},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29190492630004883},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.21294018626213074},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19932234287261963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2013.6721336","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2013.6721336","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS","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":14,"referenced_works":["https://openalex.org/W183241451","https://openalex.org/W1585385982","https://openalex.org/W2043665634","https://openalex.org/W2069231830","https://openalex.org/W2097915756","https://openalex.org/W2098057602","https://openalex.org/W2101365302","https://openalex.org/W2131697388","https://openalex.org/W2136251662","https://openalex.org/W2150579376","https://openalex.org/W2153409933","https://openalex.org/W2164330327","https://openalex.org/W4320339642","https://openalex.org/W6635184699"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440","https://openalex.org/W2343470940"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,23,92],"propose":[4],"a":[5,46,58],"new":[6],"model":[7,44,81],"for":[8],"hyperspectral":[9,37,121],"image":[10],"classification":[11,115],"using":[12],"spectral-spatial":[13],"information.":[14],"The":[15,39,79],"main":[16],"contributions":[17],"of":[18,89],"our":[19,43,126],"paper":[20],"are":[21],"that":[22,125],"exploit":[24],"the":[25,35,54,65,76,85,94,99,103,108,114],"posterior":[26,66],"distribution":[27,67],"from":[28,102],"both":[29],"spectral":[30],"and":[31,53],"spatial":[32,95,100],"information":[33,101],"in":[34,42],"original":[36],"data.":[38],"association":[40],"potential":[41,56],"is":[45,57,82],"sparse":[47],"multinomial":[48],"logistic":[49],"regression":[50],"(SMLR)":[51],"classifier":[52],"interaction":[55],"spatial-relevant":[59],"total":[60],"variation":[61],"(TV)":[62],"constraint":[63],"upon":[64],"itself":[68],"which":[69],"encourages":[70],"neighboring":[71],"pixels":[72],"to":[73,75,107,111],"belong":[74],"same":[77],"class.":[78],"proposed":[80,127],"solved":[83],"by":[84,97],"alternating":[86],"direction":[87],"method":[88],"multipliers":[90],"(ADMM);":[91],"enhance":[93],"smoothness":[96],"expanding":[98],"fixed":[104],"labeled":[105],"samples":[106],"whole":[109],"data":[110,122],"further":[112],"improve":[113],"accuracy.":[116],"Experimental":[117],"results":[118],"with":[119,134],"real":[120],"set":[123],"validate":[124],"approach":[128],"provides":[129],"good":[130],"performance":[131],"when":[132],"compared":[133],"other":[135],"state-of-the-art":[136],"methods.":[137]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}