{"id":"https://openalex.org/W4402991050","doi":"https://doi.org/10.3390/rs16193646","title":"Extraction of Alteration Information from Hyperspectral Data Base on Kernel Extreme Learning Machine","display_name":"Extraction of Alteration Information from Hyperspectral Data Base on Kernel Extreme Learning Machine","publication_year":2024,"publication_date":"2024-09-29","ids":{"openalex":"https://openalex.org/W4402991050","doi":"https://doi.org/10.3390/rs16193646"},"language":"en","primary_location":{"id":"doi:10.3390/rs16193646","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16193646","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/rs16193646","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101023962","display_name":"Shuhan Yang","orcid":"https://orcid.org/0009-0007-9741-2245"},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuhan Yang","raw_affiliation_strings":["School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China","institution_ids":["https://openalex.org/I3125743391"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111347441","display_name":"Tian Shufang","orcid":null},"institutions":[{"id":"https://openalex.org/I3125743391","display_name":"China University of Geosciences (Beijing)","ror":"https://ror.org/04q6c7p66","country_code":"CN","type":"education","lineage":["https://openalex.org/I3125743391"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shufang Tian","raw_affiliation_strings":["School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China"],"affiliations":[{"raw_affiliation_string":"School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China","institution_ids":["https://openalex.org/I3125743391"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101023962"],"corresponding_institution_ids":["https://openalex.org/I3125743391"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.8131,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.87576577,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"16","issue":"19","first_page":"3646","last_page":"3646"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.987500011920929,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.6702055931091309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5510974526405334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46735456585884094},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.46267980337142944},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.4482189416885376},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4056779742240906},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3677690625190735},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.2129165530204773}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6702055931091309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5510974526405334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46735456585884094},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.46267980337142944},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.4482189416885376},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4056779742240906},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3677690625190735},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.2129165530204773},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16193646","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16193646","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:f4c49f5049c0483eb6f1a8e3d6b55c1c","is_oa":true,"landing_page_url":"https://doaj.org/article/f4c49f5049c0483eb6f1a8e3d6b55c1c","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 16, Iss 19, p 3646 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16193646","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16193646","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2026131661","https://openalex.org/W2109606373","https://openalex.org/W2121824258","https://openalex.org/W2169877324","https://openalex.org/W2356490980","https://openalex.org/W2374932661","https://openalex.org/W2768901480","https://openalex.org/W2998553334","https://openalex.org/W3004969126","https://openalex.org/W3131502930","https://openalex.org/W3196874415","https://openalex.org/W4307897470","https://openalex.org/W4367663491","https://openalex.org/W4382519808","https://openalex.org/W4383571104","https://openalex.org/W4396766427","https://openalex.org/W4398151306","https://openalex.org/W6706382790","https://openalex.org/W6709287495","https://openalex.org/W6790799976","https://openalex.org/W6854518917","https://openalex.org/W7070854773"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W2067443264","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W1991437568","https://openalex.org/W2391683795"],"abstract_inverted_index":{"Machine":[0,48,65,135,141],"learning,":[1],"as":[2],"an":[3],"increasingly":[4],"prominent":[5],"method":[6,75,171],"in":[7,151,165,176],"recent":[8],"years,":[9],"has":[10,172],"introduced":[11],"new":[12],"methodologies":[13],"and":[14,79,84,131,147,162],"perspectives":[15],"for":[16,76,116],"extracting":[17],"geological":[18],"alteration":[19,36,117,181],"information.":[20,182],"To":[21],"enhance":[22],"the":[23,33,44,52,61,72,82,112,128,132,137,144,148,152,158,166,170,177],"accuracy":[24,146],"of":[25,35,60,179],"remote-sensing-alteration":[26],"mineral":[27,160],"information,":[28],"this":[29],"study":[30],"focuses":[31],"on":[32],"extraction":[34,153,178],"information":[37,118],"from":[38,103],"hyperspectral":[39,104,180],"remote":[40],"sensing":[41],"data":[42,102],"using":[43],"Kernel-Based":[45,138],"Extreme":[46,63,139],"Learning":[47,64,140],"(KELM)":[49],"optimized":[50],"with":[51,87],"Sparrow":[53],"Search":[54],"Algorithm":[55],"(SSA).":[56],"The":[57,120],"ideal":[58],"parameters":[59],"Kernel":[62],"model":[66,115],"were":[67,107],"successfully":[68],"acquired":[69],"by":[70,90],"utilizing":[71],"sparrow":[73],"optimization":[74],"continuous":[77],"search":[78],"iteration,":[80],"avoiding":[81],"blindness":[83],"arbitrariness":[85],"associated":[86],"parameter":[88],"selection":[89],"humans.":[91],"Spectral":[92],"Angle":[93],"Mapper":[94],"(SAM)":[95],"technology":[96],"was":[97],"used":[98,109],"to":[99,110,127],"extract":[100],"sample":[101],"imagery,":[105],"which":[106],"then":[108],"train":[111],"machine":[113],"learning":[114],"extraction.":[119],"experimental":[121],"results":[122],"show":[123],"that,":[124],"when":[125],"compared":[126],"Random":[129],"Forest":[130],"Support":[133],"Vector":[134],"algorithms,":[136],"algorithm":[142],"achieved":[143],"highest":[145],"best":[149],"effect":[150],"results.":[154],"It":[155],"closely":[156],"matches":[157],"known":[159],"points":[161],"geochemical":[163],"anomalies":[164],"area,":[167],"confirming":[168],"that":[169],"a":[173],"clear":[174],"advantage":[175]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-27T23:08:20.325037","created_date":"2025-10-10T00:00:00"}
