{"id":"https://openalex.org/W3016049991","doi":"https://doi.org/10.1109/iciis47346.2019.9063263","title":"Feature Extraction Using Minor Scatter Directions of Data to Distinguish Between Classes With Minute Differences of a Hyperspectral Image","display_name":"Feature Extraction Using Minor Scatter Directions of Data to Distinguish Between Classes With Minute Differences of a Hyperspectral Image","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3016049991","doi":"https://doi.org/10.1109/iciis47346.2019.9063263","mag":"3016049991"},"language":"en","primary_location":{"id":"doi:10.1109/iciis47346.2019.9063263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iciis47346.2019.9063263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th Conference on Industrial and Information Systems (ICIIS)","raw_type":"proceedings-article"},"type":"article","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/A5061049438","display_name":"M.M. Ekanayake","orcid":"https://orcid.org/0000-0002-4768-5073"},"institutions":[{"id":"https://openalex.org/I111199411","display_name":"University of Peradeniya","ror":"https://ror.org/025h79t26","country_code":"LK","type":"education","lineage":["https://openalex.org/I111199411"]}],"countries":["LK"],"is_corresponding":true,"raw_author_name":"E. M. M. B. Ekanayake","raw_affiliation_strings":["University of Peradeniya, Peradeniya, Sri Lanka"],"affiliations":[{"raw_affiliation_string":"University of Peradeniya, Peradeniya, Sri Lanka","institution_ids":["https://openalex.org/I111199411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027481493","display_name":"Wele Gedara Chaminda Bandara","orcid":"https://orcid.org/0000-0003-2516-2930"},"institutions":[{"id":"https://openalex.org/I111199411","display_name":"University of Peradeniya","ror":"https://ror.org/025h79t26","country_code":"LK","type":"education","lineage":["https://openalex.org/I111199411"]}],"countries":["LK"],"is_corresponding":false,"raw_author_name":"W. G. C. Bandara","raw_affiliation_strings":["University of Peradeniya, Peradeniya, Sri Lanka"],"affiliations":[{"raw_affiliation_string":"University of Peradeniya, Peradeniya, Sri Lanka","institution_ids":["https://openalex.org/I111199411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039986037","display_name":"G. W. K. Prabhath","orcid":null},"institutions":[{"id":"https://openalex.org/I111199411","display_name":"University of Peradeniya","ror":"https://ror.org/025h79t26","country_code":"LK","type":"education","lineage":["https://openalex.org/I111199411"]}],"countries":["LK"],"is_corresponding":false,"raw_author_name":"G. W. K. Prabhath","raw_affiliation_strings":["University of Peradeniya, Peradeniya, Sri Lanka"],"affiliations":[{"raw_affiliation_string":"University of Peradeniya, Peradeniya, Sri Lanka","institution_ids":["https://openalex.org/I111199411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088546755","display_name":"Roshan Godaliyadda","orcid":"https://orcid.org/0000-0002-3495-481X"},"institutions":[{"id":"https://openalex.org/I111199411","display_name":"University of Peradeniya","ror":"https://ror.org/025h79t26","country_code":"LK","type":"education","lineage":["https://openalex.org/I111199411"]}],"countries":["LK"],"is_corresponding":false,"raw_author_name":"G. M. R. I. Godaliyadda","raw_affiliation_strings":["University of Peradeniya, Peradeniya, Sri Lanka"],"affiliations":[{"raw_affiliation_string":"University of Peradeniya, Peradeniya, Sri Lanka","institution_ids":["https://openalex.org/I111199411"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022267671","display_name":"Vijitha Herath","orcid":"https://orcid.org/0000-0002-2094-0716"},"institutions":[{"id":"https://openalex.org/I111199411","display_name":"University of Peradeniya","ror":"https://ror.org/025h79t26","country_code":"LK","type":"education","lineage":["https://openalex.org/I111199411"]}],"countries":["LK"],"is_corresponding":false,"raw_author_name":"H. M. V. R. Herath","raw_affiliation_strings":["University of Peradeniya, Peradeniya, Sri Lanka"],"affiliations":[{"raw_affiliation_string":"University of Peradeniya, Peradeniya, Sri Lanka","institution_ids":["https://openalex.org/I111199411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108555949","display_name":"M. P. B. Ekanayake","orcid":null},"institutions":[{"id":"https://openalex.org/I111199411","display_name":"University of Peradeniya","ror":"https://ror.org/025h79t26","country_code":"LK","type":"education","lineage":["https://openalex.org/I111199411"]}],"countries":["LK"],"is_corresponding":false,"raw_author_name":"M. P. B. Ekanayake","raw_affiliation_strings":["University of Peradeniya, Peradeniya, Sri Lanka"],"affiliations":[{"raw_affiliation_string":"University of Peradeniya, Peradeniya, Sri Lanka","institution_ids":["https://openalex.org/I111199411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5061049438"],"corresponding_institution_ids":["https://openalex.org/I111199411"],"apc_list":null,"apc_paid":null,"fwci":0.1785,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.60310498,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"8","issue":null,"first_page":"130","last_page":"134"},"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9918000102043152,"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"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9828000068664551,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8225439786911011},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7803009152412415},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.7076354026794434},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6848084926605225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6835678219795227},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6433236002922058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6129053235054016},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.587873101234436},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5252463221549988},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.5222933292388916}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8225439786911011},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7803009152412415},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7076354026794434},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6848084926605225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6835678219795227},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6433236002922058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6129053235054016},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.587873101234436},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5252463221549988},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.5222933292388916},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iciis47346.2019.9063263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iciis47346.2019.9063263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 14th Conference on Industrial and Information Systems (ICIIS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1527548706","https://openalex.org/W2030270830","https://openalex.org/W2039409148","https://openalex.org/W2102539213","https://openalex.org/W2114217318","https://openalex.org/W2146987667","https://openalex.org/W2547686802","https://openalex.org/W2792742584","https://openalex.org/W2914214148","https://openalex.org/W2953961450","https://openalex.org/W2958871513","https://openalex.org/W2962355909","https://openalex.org/W2969514116","https://openalex.org/W2974693044","https://openalex.org/W3135020499","https://openalex.org/W6764922814","https://openalex.org/W6765714102","https://openalex.org/W6791666012"],"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":{"A":[0],"hyperspectral":[1,165],"image":[2],"(HSI)":[3],"is":[4],"a":[5,12,113,150],"compilation":[6],"of":[7,15,21,26,57,74,88,102,118,138,144,159],"grayscale":[8],"images":[9],"corresponding":[10],"to":[11,36,53,65,78,111,161,169],"wide":[13],"range":[14],"contiguous":[16],"spectral":[17,67,142],"bands.":[18],"Feature":[19],"extraction":[20,25,50,185],"HSIs":[22,63],"involves":[23],"the":[24,75,84,89,136,141,155,172,182],"informative":[27],"and":[28,46,69,148,171],"non-redundant":[29],"information":[30,56,99],"which":[31,152],"can":[32],"later":[33],"be":[34,112],"input":[35],"advance":[37],"learning":[38],"algorithms":[39],"for":[40],"various":[41],"purposes":[42],"including":[43],"classification,":[44],"clustering":[45],"unmixing.":[47],"Many":[48],"feature":[49,103,184],"techniques":[51],"fail":[52],"extract":[54],"discriminative":[55],"classes":[58,121,147,160],"with":[59,122,135],"minute":[60,123],"differences":[61,124],"in":[62,100,116,125,177],"due":[64],"similar":[66,70],"signatures":[68],"major":[71],"variance":[72,86,108,133],"directions":[73,87,109,134],"pixels":[76],"belonging":[77],"those":[79],"classes.":[80],"In":[81],"most":[82],"techniques,":[83],"minor":[85,107,132],"dataset":[90],"are":[91],"ignored":[92],"since":[93],"they":[94],"do":[95],"not":[96],"convey":[97],"useful":[98],"terms":[101,117],"extraction.":[104],"However,":[105],"these":[106,131],"prove":[110],"convenient":[114],"base":[115],"distinguishing":[119],"between":[120,140],"HSIs.":[126],"The":[127],"proposed":[128,183],"mechanism":[129,186],"exploits":[130],"implication":[137],"correlation":[139],"bands":[143],"two":[145],"individual":[146],"constructs":[149],"framework":[151],"then":[153],"utilizes":[154],"underlying":[156],"spatial":[157],"connectivity":[158],"classify":[162],"pixels.":[163],"Standard":[164],"datasets":[166],"were":[167],"subjected":[168],"testing":[170],"results":[173],"show":[174],"an":[175],"improvement":[176],"classification":[178],"accuracy":[179],"levels":[180],"after":[181],"had":[187],"been":[188],"utilized.":[189]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
