{"id":"https://openalex.org/W2554764988","doi":"https://doi.org/10.1109/lgrs.2016.2622726","title":"Fast and Accurate Spatiotemporal Fusion Based Upon Extreme Learning Machine","display_name":"Fast and Accurate Spatiotemporal Fusion Based Upon Extreme Learning Machine","publication_year":2016,"publication_date":"2016-11-18","ids":{"openalex":"https://openalex.org/W2554764988","doi":"https://doi.org/10.1109/lgrs.2016.2622726","mag":"2554764988"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2016.2622726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2016.2622726","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-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/A5039339597","display_name":"Xun Liu","orcid":"https://orcid.org/0000-0002-4805-3262"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xun Liu","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079668307","display_name":"Chenwei Deng","orcid":"https://orcid.org/0000-0002-3747-5128"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenwei Deng","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3747-5128","affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088530627","display_name":"Shuigen Wang","orcid":"https://orcid.org/0000-0003-3598-0443"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuigen Wang","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061746912","display_name":"Guang-Bin Huang","orcid":"https://orcid.org/0000-0002-2480-4965"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Guang-Bin Huang","raw_affiliation_strings":["School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100985496","display_name":"Baojun Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baojun Zhao","raw_affiliation_strings":["School of Information and Electronics, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Electronics, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065777975","display_name":"Paula Lauren","orcid":"https://orcid.org/0000-0003-3970-2280"},"institutions":[{"id":"https://openalex.org/I177721651","display_name":"Oakland University","ror":"https://ror.org/01ythxj32","country_code":"US","type":"education","lineage":["https://openalex.org/I177721651"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Paula Lauren","raw_affiliation_strings":["School of Engineering and Computer Science, Oakland University, Rochester, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Engineering and Computer Science, Oakland University, Rochester, MI, USA","institution_ids":["https://openalex.org/I177721651"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":9.2745,"has_fulltext":false,"cited_by_count":88,"citation_normalized_percentile":{"value":0.97923707,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"13","issue":"12","first_page":"2039","last_page":"2043"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998000264167786,"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":0.9998000264167786,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9966999888420105,"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/T11324","display_name":"Spectroscopy Techniques in Biomedical and Chemical Research","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7561397552490234},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.7021821141242981},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6360436677932739},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4651896059513092},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4428461492061615},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4315207898616791},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.42381593585014343},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4200066030025482},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.413600891828537},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4039381146430969},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.25212880969047546},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.21921801567077637},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12976229190826416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7561397552490234},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7021821141242981},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6360436677932739},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4651896059513092},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4428461492061615},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4315207898616791},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.42381593585014343},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4200066030025482},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.413600891828537},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4039381146430969},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25212880969047546},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.21921801567077637},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12976229190826416},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2016.2622726","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2016.2622726","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6560842136","display_name":null,"funder_award_id":"61301090","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1588434184","https://openalex.org/W1982956952","https://openalex.org/W1998349423","https://openalex.org/W2003059629","https://openalex.org/W2003224325","https://openalex.org/W2023306858","https://openalex.org/W2026131661","https://openalex.org/W2027776168","https://openalex.org/W2050225888","https://openalex.org/W2055576996","https://openalex.org/W2056811372","https://openalex.org/W2060173047","https://openalex.org/W2061065224","https://openalex.org/W2088603520","https://openalex.org/W2111072639","https://openalex.org/W2121025662","https://openalex.org/W2133665775","https://openalex.org/W2151456308","https://openalex.org/W2301541953","https://openalex.org/W2343558730"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W31566076","https://openalex.org/W4297902562","https://openalex.org/W2741186499","https://openalex.org/W2804652951","https://openalex.org/W2968645206","https://openalex.org/W2556335056","https://openalex.org/W2002678693","https://openalex.org/W2743832667","https://openalex.org/W2554736181"],"abstract_inverted_index":{"Spatiotemporal":[0],"fusion":[1,19,90,181],"is":[2,60,92,142,155],"important":[3],"in":[4,79,94],"providing":[5],"high":[6],"spatial":[7],"resolution":[8,46,168],"earth":[9],"observations":[10],"with":[11,35],"a":[12,32,39,87,98,114,129],"dense":[13],"time":[14],"series,":[15],"and":[16,64,137,147,172],"recently,":[17],"learning-based":[18],"methods":[20],"have":[21],"been":[22],"attracting":[23],"broad":[24],"interest.":[25],"These":[26],"algorithms":[27],"project":[28],"image":[29],"patches":[30,47,150],"onto":[31],"feature":[33,125],"space":[34],"the":[36,44,49,54,80,123,140],"enforcement":[37],"of":[38,162],"simple":[40,130],"mapping":[41,115],"to":[42,66,112,144],"predict":[43],"fine":[45,149],"from":[48],"corresponding":[50],"coarse":[51,81],"ones.":[52],"However,":[53],"sophisticated":[55,124],"projection,":[56],"e.g.,":[57],"sparse":[58],"representation,":[59],"always":[61],"computationally":[62],"complex":[63],"difficult":[65],"be":[67],"implemented":[68],"on":[69,117],"large":[70],"patches,":[71],"which":[72],"cannot":[73],"grasp":[74],"enough":[75],"local":[76],"structural":[77],"information":[78],"patches.":[82],"To":[83],"address":[84],"these":[85],"issues,":[86],"novel":[88],"spatiotemporal":[89],"method":[91,178],"proposed":[93,153],"this":[95],"letter,":[96],"using":[97],"powerful":[99],"learning":[100,104,113],"technique,":[101],"i.e.,":[102],"extreme":[103],"machine":[105],"(ELM).":[106],"Unlike":[107],"traditional":[108],"approaches,":[109],"we":[110],"devote":[111],"function":[116],"difference":[118],"images":[119],"directly,":[120],"rather":[121],"than":[122],"representation":[126],"followed":[127],"by":[128,133,157],"mapping.":[131],"Characterized":[132],"good":[134],"generalization":[135],"performance":[136],"fast":[138,148],"speed,":[139],"ELM":[141],"employed":[143],"achieve":[145],"accurate":[146],"prediction.":[151],"The":[152],"algorithm":[154],"evaluated":[156],"five":[158],"actual":[159],"data":[160],"sets":[161],"Landsat":[163],"enhanced":[164],"thematic":[165],"mapper":[166],"plus-moderate":[167],"imaging":[169],"spectroradiometer":[170],"acquisitions":[171],"experimental":[173],"results":[174,182],"show":[175],"that":[176],"our":[177],"obtains":[179],"better":[180],"while":[183],"achieving":[184],"much":[185],"greater":[186],"speed.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":16},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}