{"id":"https://openalex.org/W2132816823","doi":"https://doi.org/10.5430/air.v1n1p63","title":"Hyperspectral image classification incorporating bacterial foraging-optimized spectral weighting","display_name":"Hyperspectral image classification incorporating bacterial foraging-optimized spectral weighting","publication_year":2012,"publication_date":"2012-08-01","ids":{"openalex":"https://openalex.org/W2132816823","doi":"https://doi.org/10.5430/air.v1n1p63","mag":"2132816823"},"language":"en","primary_location":{"id":"doi:10.5430/air.v1n1p63","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v1n1p63","pdf_url":"https://www.sciedupress.com/journal/index.php/air/article/download/844/804","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://www.sciedupress.com/journal/index.php/air/article/download/844/804","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074220429","display_name":"Ankush Chakrabarty","orcid":"https://orcid.org/0000-0001-9637-854X"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ankush Chakrabarty","raw_affiliation_strings":["Purdue University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University","institution_ids":["https://openalex.org/I219193219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011221704","display_name":"Olivia Choudhury","orcid":"https://orcid.org/0000-0002-5009-4397"},"institutions":[{"id":"https://openalex.org/I16019930","display_name":"Saha Institute of Nuclear Physics","ror":"https://ror.org/0491yz035","country_code":"IN","type":"facility","lineage":["https://openalex.org/I16019930"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Olivia Choudhury","raw_affiliation_strings":[". Computer Science Department, Meghnad Saha Institute of Technology, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":". Computer Science Department, Meghnad Saha Institute of Technology, Kolkata, India","institution_ids":["https://openalex.org/I16019930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109500805","display_name":"Pallab Sarkar","orcid":null},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pallab Sarkar","raw_affiliation_strings":[". Electrical Engineering Department, Jadavpur University, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":". Electrical Engineering Department, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066170767","display_name":"Avishek Paul","orcid":"https://orcid.org/0000-0002-5611-1397"},"institutions":[{"id":"https://openalex.org/I170979836","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012","country_code":"IN","type":"education","lineage":["https://openalex.org/I170979836"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Avishek Paul","raw_affiliation_strings":[". Electrical Engineering Department, Jadavpur University, Kolkata, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":". Electrical Engineering Department, Jadavpur University, Kolkata, India","institution_ids":["https://openalex.org/I170979836"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041652285","display_name":"Debarghya Sarkar","orcid":"https://orcid.org/0000-0002-5411-7066"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Debarghya Sarkar","raw_affiliation_strings":["Electrical Engineering Department, Purdue University, West Lafayette, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, Purdue University, West Lafayette, USA","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0298,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.81419588,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"1","issue":"1","first_page":"63","last_page":"63"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9915000200271606,"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"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.989300012588501,"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":0.853650689125061},{"id":"https://openalex.org/keywords/imaging-spectrometer","display_name":"Imaging spectrometer","score":0.7169404625892639},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7060990333557129},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6222140789031982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6005894541740417},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5946965217590332},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5495535135269165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5259718298912048},{"id":"https://openalex.org/keywords/vnir","display_name":"VNIR","score":0.4966891407966614},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.47506970167160034},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.47376731038093567},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.44624465703964233},{"id":"https://openalex.org/keywords/spectrometer","display_name":"Spectrometer","score":0.2666087746620178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2266368269920349},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11350885033607483}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.853650689125061},{"id":"https://openalex.org/C183852935","wikidata":"https://www.wikidata.org/wiki/Q6002848","display_name":"Imaging spectrometer","level":3,"score":0.7169404625892639},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7060990333557129},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6222140789031982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6005894541740417},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5946965217590332},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5495535135269165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5259718298912048},{"id":"https://openalex.org/C5457282","wikidata":"https://www.wikidata.org/wiki/Q7907352","display_name":"VNIR","level":3,"score":0.4966891407966614},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.47506970167160034},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.47376731038093567},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.44624465703964233},{"id":"https://openalex.org/C33390570","wikidata":"https://www.wikidata.org/wiki/Q188463","display_name":"Spectrometer","level":2,"score":0.2666087746620178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2266368269920349},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11350885033607483},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5430/air.v1n1p63","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v1n1p63","pdf_url":"https://www.sciedupress.com/journal/index.php/air/article/download/844/804","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.5430/air.v1n1p63","is_oa":true,"landing_page_url":"https://doi.org/10.5430/air.v1n1p63","pdf_url":"https://www.sciedupress.com/journal/index.php/air/article/download/844/804","source":{"id":"https://openalex.org/S4210167461","display_name":"Artificial Intelligence Research","issn_l":"1927-6974","issn":["1927-6974","1927-6982"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320842","host_organization_name":"Sciedu Press","host_organization_lineage":["https://openalex.org/P4310320842"],"host_organization_lineage_names":["Sciedu Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Artificial Intelligence Research","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6200000047683716,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320309036","display_name":"Purdue University","ror":"https://ror.org/02dqehb95"},{"id":"https://openalex.org/F4320311382","display_name":"Jadavpur University","ror":"https://ror.org/02af4h012"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2132816823.pdf","grobid_xml":"https://content.openalex.org/works/W2132816823.grobid-xml"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W628438000","https://openalex.org/W1513817866","https://openalex.org/W1560724230","https://openalex.org/W1568892534","https://openalex.org/W1601740268","https://openalex.org/W1639032689","https://openalex.org/W1661766053","https://openalex.org/W1978786559","https://openalex.org/W2010797000","https://openalex.org/W2014158063","https://openalex.org/W2029784482","https://openalex.org/W2078619499","https://openalex.org/W2082897930","https://openalex.org/W2094959198","https://openalex.org/W2098057602","https://openalex.org/W2102343719","https://openalex.org/W2103545758","https://openalex.org/W2104128541","https://openalex.org/W2104269704","https://openalex.org/W2113464037","https://openalex.org/W2118996198","https://openalex.org/W2119821739","https://openalex.org/W2120426270","https://openalex.org/W2121169814","https://openalex.org/W2122122715","https://openalex.org/W2122301197","https://openalex.org/W2130774035","https://openalex.org/W2131697388","https://openalex.org/W2133950995","https://openalex.org/W2134231130","https://openalex.org/W2135646341","https://openalex.org/W2136251662","https://openalex.org/W2137685701","https://openalex.org/W2139212933","https://openalex.org/W2143560894","https://openalex.org/W2144205029","https://openalex.org/W2148603752","https://openalex.org/W2148842444","https://openalex.org/W2150796457","https://openalex.org/W2153608551","https://openalex.org/W2153635508","https://openalex.org/W2161278885","https://openalex.org/W2161372002","https://openalex.org/W2162698522","https://openalex.org/W2164769329","https://openalex.org/W2165049595","https://openalex.org/W2312997001","https://openalex.org/W2402846924","https://openalex.org/W2478493250","https://openalex.org/W2530938137","https://openalex.org/W2533149454","https://openalex.org/W2543580944","https://openalex.org/W2554421890","https://openalex.org/W3023540311","https://openalex.org/W3099514962","https://openalex.org/W3120421331","https://openalex.org/W3193477162","https://openalex.org/W3195149063","https://openalex.org/W4200394859","https://openalex.org/W4239510810","https://openalex.org/W4292023222","https://openalex.org/W6651708705","https://openalex.org/W6703967216"],"related_works":["https://openalex.org/W2809209827","https://openalex.org/W4387802641","https://openalex.org/W2027460042","https://openalex.org/W2746742660","https://openalex.org/W2045337428","https://openalex.org/W2044082451","https://openalex.org/W2542688861","https://openalex.org/W2801095402","https://openalex.org/W2082586825","https://openalex.org/W2119473622"],"abstract_inverted_index":{"The":[0,21,50,67,115],"present":[1],"paper":[2],"describes":[3],"the":[4,26,30,38,57,70,103,121,138,141,178,181],"development":[5],"of":[6,29,62,69,87,140,180],"a":[7,44],"hyperspectral":[8,65,83],"image":[9],"classification":[10,160],"scheme":[11],"using":[12,32,37,120],"support":[13],"vector":[14],"machines":[15],"(SVM)":[16],"with":[17,151],"spectrally":[18],"weighted":[19],"kernels.":[20],"kernels":[22],"are":[23,54],"designed":[24],"during":[25],"training":[27],"phase":[28],"SVM":[31,58],"optimal":[33],"spectral":[34],"weights":[35],"estimated":[36],"Bacterial":[39],"Foraging":[40],"Optimization":[41],"(BFO)":[42],"algorithm,":[43],"popular":[45],"modern":[46],"stochastic":[47,196],"optimization":[48],"algorithm.":[49],"optimized":[51],"kernel":[52],"functions":[53],"then":[55],"in":[56,64,144,174,191],"paradigm":[59],"for":[60,156,162],"bi-classification":[61],"pixels":[63],"images.":[66],"effectiveness":[68],"proposed":[71,142],"approach":[72,143],"is":[73,184],"demonstrated":[74],"by":[75,102],"implementing":[76],"it":[77],"on":[78],"three":[79],"widely":[80],"used":[81],"benchmark":[82],"data":[84],"sets,":[85],"two":[86],"which":[88],"were":[89,166],"taken":[90],"over":[91,128],"agricultural":[92,152],"sites":[93],"at":[94,110,132],"Indian":[95],"Pines,":[96],"Indiana,":[97],"and":[98,159,168],"Salinas":[99],"Valley,":[100],"California,":[101],"Airborne":[104],"Visible":[105],"Infra-Red":[106],"Imaging":[107,125],"Spectrometer":[108,126],"(AVIRIS)":[109],"NASA\u2019s":[111],"Jet":[112],"Propulsion":[113],"Laboratory.":[114],"third":[116],"dataset":[117],"was":[118],"acquired":[119],"Reflective":[122],"Optical":[123],"System":[124],"(ROSIS)":[127],"an":[129,145],"urban":[130,146],"scene":[131],"Pavia":[133],"University,":[134],"Italy":[135],"to":[136,170,187,193],"demonstrate":[137],"efficacy":[139],"scenario":[147],"as":[148,150],"well":[149],"data.":[153],"Classification":[154],"errors":[155],"One-Against-One":[157],"(OAO)":[158],"accuracies":[161],"One-Against-All":[163],"(OAA)":[164],"schemes":[165],"computed":[167],"compared":[169],"other":[171,194],"methods":[172],"developed":[173],"recent":[175],"times.":[176],"Finally,":[177],"use":[179],"BFO-based":[182],"technique":[183],"recommended":[185],"owing":[186],"its":[188],"superior":[189],"performance,":[190],"comparison":[192],"contemporary":[195],"bio-inspired":[197],"algorithms.":[198]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}