{"id":"https://openalex.org/W3175258615","doi":"https://doi.org/10.1155/2021/5592323","title":"A Search Method for Optimal Band Combination of Hyperspectral Imagery Based on Two Layers Selection Strategy","display_name":"A Search Method for Optimal Band Combination of Hyperspectral Imagery Based on Two Layers Selection Strategy","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3175258615","doi":"https://doi.org/10.1155/2021/5592323","mag":"3175258615","pmid":"https://pubmed.ncbi.nlm.nih.gov/34239549"},"language":"en","primary_location":{"id":"doi:10.1155/2021/5592323","is_oa":true,"landing_page_url":"http://doi.org/10.1155/2021/5592323","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/5592323.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/cin/2021/5592323.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101602848","display_name":"Nian Chen","orcid":"https://orcid.org/0000-0002-8816-1233"},"institutions":[{"id":"https://openalex.org/I4210089621","display_name":"Chizhou University","ror":"https://ror.org/007cx7r28","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210089621"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Nian Chen","raw_affiliation_strings":["School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China","institution_ids":["https://openalex.org/I4210089621"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013535667","display_name":"Kezhong Lu","orcid":"https://orcid.org/0000-0001-7803-4639"},"institutions":[{"id":"https://openalex.org/I4210089621","display_name":"Chizhou University","ror":"https://ror.org/007cx7r28","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210089621"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kezhong Lu","raw_affiliation_strings":["College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China","School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China","institution_ids":["https://openalex.org/I4210089621"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029175864","display_name":"Hao Zhou","orcid":"https://orcid.org/0000-0002-0717-6784"},"institutions":[{"id":"https://openalex.org/I4210089621","display_name":"Chizhou University","ror":"https://ror.org/007cx7r28","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210089621"]},{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Zhou","raw_affiliation_strings":["College of Computer and Information Science, Southwest University, Chongqing 400715, China","School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, Southwest University, Chongqing 400715, China","institution_ids":["https://openalex.org/I142108993"]},{"raw_affiliation_string":"School of Big Data and Artificial Intelligence, Chizhou University, Chizhou 247000, China","institution_ids":["https://openalex.org/I4210089621"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101602848"],"corresponding_institution_ids":["https://openalex.org/I4210089621"],"apc_list":{"value":2100,"currency":"USD","value_usd":2100},"apc_paid":{"value":2100,"currency":"USD","value_usd":2100},"fwci":0.126,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.46865138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2021","issue":"1","first_page":"5592323","last_page":"5592323"},"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":0.972599983215332,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9652000069618225,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7608783841133118},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6322577595710754},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.629347562789917},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6222869753837585},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.616071343421936},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6065084338188171},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5742110013961792},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.5690768361091614},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5217127203941345},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.5051344037055969},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.45664188265800476},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.41234713792800903},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37170127034187317},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3158748745918274},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16672268509864807}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7608783841133118},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6322577595710754},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.629347562789917},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6222869753837585},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.616071343421936},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6065084338188171},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5742110013961792},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.5690768361091614},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5217127203941345},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.5051344037055969},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.45664188265800476},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.41234713792800903},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37170127034187317},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3158748745918274},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16672268509864807},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":5,"locations":[{"id":"doi:10.1155/2021/5592323","is_oa":true,"landing_page_url":"http://doi.org/10.1155/2021/5592323","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/5592323.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},{"id":"pmid:34239549","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34239549","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational intelligence and neuroscience","raw_type":null},{"id":"pmh:oai:doaj.org/article:930a4bc5abcc45249f76319caf18273a","is_oa":true,"landing_page_url":"https://doaj.org/article/930a4bc5abcc45249f76319caf18273a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Intelligence and Neuroscience, Vol 2021 (2021)","raw_type":"article"},{"id":"pmh:oai:hindawi.com:10.1155/2021/5592323","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2021/5592323","pdf_url":null,"source":{"id":"https://openalex.org/S4306400340","display_name":"Hindawi Journal of Chemistry (Hindawi)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210126990","host_organization_name":"Hindawi (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210126990"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Research Article"},{"id":"pmh:oai:pubmedcentral.nih.gov:8241513","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8241513","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Comput Intell Neurosci","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1155/2021/5592323","is_oa":true,"landing_page_url":"http://doi.org/10.1155/2021/5592323","pdf_url":"https://downloads.hindawi.com/journals/cin/2021/5592323.pdf","source":{"id":"https://openalex.org/S72372694","display_name":"Computational Intelligence and Neuroscience","issn_l":"1687-5265","issn":["1687-5265","1687-5273"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Intelligence and Neuroscience","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3175258615.pdf","grobid_xml":"https://content.openalex.org/works/W3175258615.grobid-xml"},"referenced_works_count":33,"referenced_works":["https://openalex.org/W1673310716","https://openalex.org/W1967275758","https://openalex.org/W1996510517","https://openalex.org/W2001914975","https://openalex.org/W2008641145","https://openalex.org/W2011430131","https://openalex.org/W2053762059","https://openalex.org/W2071821878","https://openalex.org/W2098057602","https://openalex.org/W2109836508","https://openalex.org/W2138038253","https://openalex.org/W2150566919","https://openalex.org/W2150990614","https://openalex.org/W2153233077","https://openalex.org/W2161815745","https://openalex.org/W2165232124","https://openalex.org/W2165835468","https://openalex.org/W2188193460","https://openalex.org/W2219715551","https://openalex.org/W2288723698","https://openalex.org/W2520037496","https://openalex.org/W2524847239","https://openalex.org/W2549636757","https://openalex.org/W2609085675","https://openalex.org/W2734337707","https://openalex.org/W2762629333","https://openalex.org/W2763486888","https://openalex.org/W2789249105","https://openalex.org/W2807146096","https://openalex.org/W2953618482","https://openalex.org/W3007826101","https://openalex.org/W4231029117","https://openalex.org/W6903340772"],"related_works":["https://openalex.org/W2132083814","https://openalex.org/W2292979300","https://openalex.org/W1995622179","https://openalex.org/W1484111231","https://openalex.org/W4391160746","https://openalex.org/W1552543208","https://openalex.org/W2074396517","https://openalex.org/W2166963679","https://openalex.org/W2187269125","https://openalex.org/W1641615907"],"abstract_inverted_index":{"A":[0],"band":[1],"selection":[2,8,124,145],"method":[3],"based":[4],"on":[5,177],"two":[6,70],"layers":[7],"(TLS)":[9],"strategy,":[10],"which":[11],"forms":[12],"an":[13],"optimal":[14],"subset":[15],"from":[16],"all-bands":[17],"set":[18,62,95,149],"to":[19,28,63,82,91,115,128],"reconstitute":[20],"the":[21,48,60,73,84,99,103,111,117,123,147,160,167,183,190],"original":[22],"hyperspectral":[23],"imagery":[24],"(HSI)":[25],"and":[26,53,106,109,153,159,195,198,211],"aims":[27],"cost":[29],"a":[30,54,93,143],"fewer":[31],"bands":[32,49,191],"for":[33,67],"better":[34],"performances,":[35],"is":[36,80,125],"proposed":[37],"in":[38,88,132,136,146,202],"this":[39],"paper.":[40],"As":[41],"its":[42],"name":[43],"implies,":[44],"TLS":[45,187],"picks":[46],"out":[47,131],"with":[50,171,192],"low":[51],"correlation":[52,194],"large":[55],"amount":[56],"of":[57,119,156,204],"information":[58,157,197],"into":[59,166],"target":[61,168],"reach":[64],"dimensionality":[65],"reduction":[66],"HSI":[68,180],"via":[69],"phases.":[71],"Specifically,":[72],"fast":[74],"density":[75,105,120],"peaks":[76],"clustering":[77],"(FDPC)":[78],"algorithm":[79],"used":[81],"select":[83],"most":[85],"representative":[86],"node":[87],"each":[89],"cluster":[90],"build":[92],"candidate":[94,148],"at":[96],"first.":[97],"During":[98],"implementation,":[100],"we":[101,141],"normalize":[102],"local":[104],"relative":[107],"distance":[108,114],"utilize":[110],"dynamic":[112],"cutoff":[113],"weaken":[116],"influence":[118],"so":[121],"that":[122,186],"more":[126],"likely":[127],"be":[129,164],"carried":[130],"scattered":[133],"clusters":[134],"than":[135],"high-density":[137],"ones.":[138],"After":[139],"that,":[140],"conduct":[142],"further":[144],"using":[150],"mRMR":[151],"strategy":[152],"comprehensive":[154],"measurement":[155],"(CMI),":[158],"eventual":[161],"winners":[162],"will":[163],"selected":[165],"set.":[169],"Compared":[170],"other":[172],"six":[173],"state-of-the-art":[174],"unsupervised":[175],"algorithms":[176],"three":[178],"real-world":[179],"data":[181],"sets,":[182],"results":[184],"show":[185],"can":[188],"group":[189],"lower":[193],"richer":[196],"has":[199],"obvious":[200],"advantages":[201],"indicators":[203],"overall":[205],"accuracy":[206,209],"(OA),":[207],"average":[208],"(AA),":[210],"Kappa":[212],"coefficient.":[213]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
