{"id":"https://openalex.org/W1986883641","doi":"https://doi.org/10.1109/cec.2010.5586533","title":"Affinity propagation based memetic band selection on hyperspectral imagery datasets","display_name":"Affinity propagation based memetic band selection on hyperspectral imagery datasets","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W1986883641","doi":"https://doi.org/10.1109/cec.2010.5586533","mag":"1986883641"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2010.5586533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2010.5586533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Congress on Evolutionary Computation","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/A5052762681","display_name":"Zexuan Zhu","orcid":"https://orcid.org/0000-0001-8479-6904"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zexuan Zhu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","College of Computer Science and Software Engineering, Shenzhen University Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035753061","display_name":"Sen Jia","orcid":"https://orcid.org/0000-0001-9742-5037"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sen Jia","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","College of Computer Science and Software Engineering, Shenzhen University Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025341885","display_name":"Zhen Ji","orcid":"https://orcid.org/0000-0003-4006-7456"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhen Ji","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","College of Computer Science and Software Engineering, Shenzhen University Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9750999808311462,"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":0.911300003528595,"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":0.9001239538192749},{"id":"https://openalex.org/keywords/memetic-algorithm","display_name":"Memetic algorithm","score":0.7308124899864197},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6585118770599365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6313201785087585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5995790362358093},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5636230707168579},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5151365995407104},{"id":"https://openalex.org/keywords/genetic-algorithm","display_name":"Genetic algorithm","score":0.5037190318107605},{"id":"https://openalex.org/keywords/affinity-propagation","display_name":"Affinity propagation","score":0.42690014839172363},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28190553188323975},{"id":"https://openalex.org/keywords/evolutionary-algorithm","display_name":"Evolutionary algorithm","score":0.25215595960617065},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.20329371094703674}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9001239538192749},{"id":"https://openalex.org/C35129592","wikidata":"https://www.wikidata.org/wiki/Q324793","display_name":"Memetic algorithm","level":3,"score":0.7308124899864197},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6585118770599365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6313201785087585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5995790362358093},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5636230707168579},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5151365995407104},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5037190318107605},{"id":"https://openalex.org/C109659709","wikidata":"https://www.wikidata.org/wiki/Q3407504","display_name":"Affinity propagation","level":5,"score":0.42690014839172363},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28190553188323975},{"id":"https://openalex.org/C159149176","wikidata":"https://www.wikidata.org/wiki/Q14489129","display_name":"Evolutionary algorithm","level":2,"score":0.25215595960617065},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.20329371094703674},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2010.5586533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2010.5586533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Congress on Evolutionary Computation","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":30,"referenced_works":["https://openalex.org/W757031997","https://openalex.org/W1500895378","https://openalex.org/W1532610010","https://openalex.org/W1659842140","https://openalex.org/W1787544972","https://openalex.org/W2019683663","https://openalex.org/W2040589129","https://openalex.org/W2057752717","https://openalex.org/W2075779886","https://openalex.org/W2087327261","https://openalex.org/W2097437812","https://openalex.org/W2100253618","https://openalex.org/W2105494575","https://openalex.org/W2114620686","https://openalex.org/W2122510010","https://openalex.org/W2125055259","https://openalex.org/W2125880329","https://openalex.org/W2133462743","https://openalex.org/W2135190479","https://openalex.org/W2136251662","https://openalex.org/W2150990614","https://openalex.org/W2154047522","https://openalex.org/W2155262811","https://openalex.org/W2156571267","https://openalex.org/W2165232124","https://openalex.org/W2165885026","https://openalex.org/W4248253651","https://openalex.org/W6622104397","https://openalex.org/W6638021218","https://openalex.org/W6682904970"],"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/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2019190440"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3],"novel":[4],"affinity":[5],"propagation":[6],"(AP)":[7],"based":[8,22,29,40,65],"memetic":[9],"band":[10,102,110],"selection":[11,75],"method":[12,19],"(APMA)":[13],"for":[14],"hyperspectral":[15,78],"imagery":[16,79],"classification.":[17],"The":[18],"incorporates":[20],"AP":[21,39,64],"local":[23,41],"search":[24,31,42],"and":[25,51,67,69,107],"genetic":[26],"algorithm":[27],"(GA)":[28],"global":[30],"to":[32,58],"take":[33],"advantage":[34],"of":[35,86],"both.":[36],"Particularly,":[37],"the":[38,44,59,70,101],"fine-tunes":[43],"GA":[45,73],"individuals":[46],"by":[47],"adding":[48],"relevant":[49],"bands":[50],"eliminating":[52],"irrelevant/redundant":[53],"bands.":[54],"A":[55],"comparison":[56],"study":[57],"filters":[60],"methods":[61],"(including":[62],"ReliefF,":[63],"method,":[66],"FCBF)":[68],"counterpart":[71],"wrapper":[72],"feature":[74],"on":[76],"two":[77],"datasets":[80],"demonstrates":[81],"that":[82],"APMA":[83,99],"is":[84],"capable":[85],"attaining":[87],"competitive":[88],"or":[89],"better":[90,109],"classification":[91],"accuracy":[92],"with":[93],"fewer":[94],"selected":[95],"bands,":[96],"which":[97],"suggests":[98],"searches":[100],"subset":[103],"space":[104],"more":[105],"efficiently":[106],"identify":[108],"subsets.":[111]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}