{"id":"https://openalex.org/W2588319717","doi":"https://doi.org/10.1109/cisp-bmei.2016.7852892","title":"Band selection based on genetic algorithms for classification of hyperspectral data","display_name":"Band selection based on genetic algorithms for classification of hyperspectral data","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2588319717","doi":"https://doi.org/10.1109/cisp-bmei.2016.7852892","mag":"2588319717"},"language":"en","primary_location":{"id":"doi:10.1109/cisp-bmei.2016.7852892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2016.7852892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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/A5059141031","display_name":"Gaojin Wen","orcid":"https://orcid.org/0000-0002-8681-7147"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaojin Wen","raw_affiliation_strings":["Laboratory of Aerial Optical Remote Sense, Beijing Institute of Space Mechanics and Electricity, Beijing, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Aerial Optical Remote Sense, Beijing Institute of Space Mechanics and Electricity, Beijing, P.R. China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100644952","display_name":"Chunxiao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chunxiao Zhang","raw_affiliation_strings":["Laboratory of Aerial Optical Remote Sense, Beijing Institute of Space Mechanics and Electricity, Beijing, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Aerial Optical Remote Sense, Beijing Institute of Space Mechanics and Electricity, Beijing, P.R. China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007744568","display_name":"Zhaorong Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaorong Lin","raw_affiliation_strings":["Laboratory of Aerial Optical Remote Sense, Beijing Institute of Space Mechanics and Electricity, Beijing, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Aerial Optical Remote Sense, Beijing Institute of Space Mechanics and Electricity, Beijing, P.R. China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108475964","display_name":"Yun Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145278","display_name":"Institute of Applied Physics and Computational Mathematics","ror":"https://ror.org/03sxpbt26","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210145278"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Xu","raw_affiliation_strings":["Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing, PR China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Computational Physics, Institute of Applied Physics and Computational Mathematics, Beijing, PR China","institution_ids":["https://openalex.org/I4210145278"]}]}],"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":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1173","last_page":"1177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9779000282287598,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9689000248908997,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.921989917755127},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.712748110294342},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6475377082824707},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6213165521621704},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6049667596817017},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5668148398399353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5568764209747314},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5498334765434265},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.5406283140182495},{"id":"https://openalex.org/keywords/data-classification","display_name":"Data classification","score":0.4521898031234741},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4251115322113037},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.40983837842941284},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3403913974761963},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2633811831474304},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23160690069198608}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.921989917755127},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.712748110294342},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6475377082824707},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6213165521621704},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6049667596817017},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5668148398399353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5568764209747314},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5498334765434265},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.5406283140182495},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.4521898031234741},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4251115322113037},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40983837842941284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3403913974761963},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2633811831474304},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23160690069198608},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cisp-bmei.2016.7852892","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cisp-bmei.2016.7852892","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 9th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","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":22,"referenced_works":["https://openalex.org/W1970945970","https://openalex.org/W1998030734","https://openalex.org/W2007008929","https://openalex.org/W2014327494","https://openalex.org/W2036842392","https://openalex.org/W2037935179","https://openalex.org/W2069556841","https://openalex.org/W2086860003","https://openalex.org/W2090091537","https://openalex.org/W2097169398","https://openalex.org/W2097900616","https://openalex.org/W2100253618","https://openalex.org/W2100383651","https://openalex.org/W2105393881","https://openalex.org/W2117756363","https://openalex.org/W2122985829","https://openalex.org/W2151419026","https://openalex.org/W2154877881","https://openalex.org/W2158400785","https://openalex.org/W2750378047","https://openalex.org/W6675463158","https://openalex.org/W6677227432"],"related_works":["https://openalex.org/W2371570177","https://openalex.org/W2596054022","https://openalex.org/W4398199373","https://openalex.org/W2740479052","https://openalex.org/W1529156857","https://openalex.org/W2168920113","https://openalex.org/W3202881146","https://openalex.org/W3001331467","https://openalex.org/W3199023014","https://openalex.org/W2357721021"],"abstract_inverted_index":{"As":[0],"an":[1],"effective":[2],"approach":[3],"for":[4,40,124],"reducing":[5],"hyperspectral":[6,41,64,122],"data":[7,42,65,123],"dimension,":[8],"band":[9,37,68,83],"selection":[10,38,84],"has":[11],"been":[12],"widely":[13],"used":[14],"in":[15,43],"the":[16,29,56,71,78,82,99,104,138,151],"fields":[17],"of":[18,22,49,63,102,109,126],"classification":[19,58,79,110,125],"and":[20,28,92,129,147],"identification":[21],"specific":[23,100],"objects.":[24],"Combining":[25],"genetic":[26,90],"algorithm":[27],"k-means":[30,93],"clustering":[31,94],"method,":[32],"we":[33,54],"propose":[34],"a":[35],"new":[36],"method":[39,59,85,117,140],"this":[44],"paper.":[45],"It":[46,134],"is":[47,75,86,118,135],"composed":[48],"three":[50],"main":[51],"steps.":[52],"First,":[53],"apply":[55],"K-means":[57],"to":[60],"cluster":[61],"bands":[62,106,149],"into":[66],"several":[67],"sets.":[69],"Second,":[70],"cost":[72],"function":[73],"criterion":[74],"constructed":[76],"from":[77],"accuracy.":[80],"Finally,":[81],"developed":[87],"based":[88],"on":[89,120],"algorithms":[91],"supervised":[95],"classifications.":[96],"In":[97],"result,":[98],"target":[101],"obtaining":[103],"least":[105],"without":[107],"loss":[108],"accuracy":[111,146],"can":[112,141],"be":[113],"obtained.":[114],"The":[115],"proposed":[116],"verified":[119],"real":[121],"plant":[127],"leaves":[128],"compared":[130],"with":[131,144],"classical":[132],"methods.":[133],"proved":[136],"that":[137],"presented":[139],"generate":[142],"results":[143],"higher":[145],"fewer":[148],"at":[150],"same":[152],"time.":[153]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
