{"id":"https://openalex.org/W2900524165","doi":"https://doi.org/10.1109/igarss.2018.8518885","title":"Joint Feature Extraction for Multispectral and Panchromatic Images Based on Convolutional Neural Network","display_name":"Joint Feature Extraction for Multispectral and Panchromatic Images Based on Convolutional Neural Network","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900524165","doi":"https://doi.org/10.1109/igarss.2018.8518885","mag":"2900524165"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","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/A5100419302","display_name":"Yi Chen","orcid":"https://orcid.org/0009-0005-7944-9349"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Chen","raw_affiliation_strings":["College of Information Science & Technology, Beijing University of Chemical Technology"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100442192","display_name":"Mengmeng Zhang","orcid":"https://orcid.org/0000-0002-5724-9785"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengmeng Zhang","raw_affiliation_strings":["College of Information Science & Technology, Beijing University of Chemical Technology"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317994","display_name":"Wei Li","orcid":"https://orcid.org/0000-0001-7015-7335"},"institutions":[{"id":"https://openalex.org/I75390827","display_name":"Beijing University of Chemical Technology","ror":"https://ror.org/00df5yc52","country_code":"CN","type":"education","lineage":["https://openalex.org/I75390827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["College of Information Science & Technology, Beijing University of Chemical Technology"],"affiliations":[{"raw_affiliation_string":"College of Information Science & Technology, Beijing University of Chemical Technology","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033017179","display_name":"Qian Du","orcid":"https://orcid.org/0000-0001-8354-7500"},"institutions":[{"id":"https://openalex.org/I99041443","display_name":"Mississippi State University","ror":"https://ror.org/0432jq872","country_code":"US","type":"education","lineage":["https://openalex.org/I4210141039","https://openalex.org/I99041443"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qian Du","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Mississippi State University"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100419302"],"corresponding_institution_ids":["https://openalex.org/I75390827"],"apc_list":null,"apc_paid":null,"fwci":0.2057,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.5949529,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"5005","last_page":"5008"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9983999729156494,"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":0.9962999820709229,"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/panchromatic-film","display_name":"Panchromatic film","score":0.9858231544494629},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.9048142433166504},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7383231520652771},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7051447629928589},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6454190015792847},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6320133805274963},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.6145749688148499},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5102512836456299},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5061797499656677},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.5037645697593689},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4801182746887207},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.43613487482070923},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43591535091400146},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.29701513051986694},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1091194748878479}],"concepts":[{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.9858231544494629},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.9048142433166504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7383231520652771},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7051447629928589},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6454190015792847},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6320133805274963},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.6145749688148499},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5102512836456299},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5061797499656677},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.5037645697593689},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4801182746887207},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.43613487482070923},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43591535091400146},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.29701513051986694},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1091194748878479},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1975869625","https://openalex.org/W1976416886","https://openalex.org/W2135402872","https://openalex.org/W2136530150","https://openalex.org/W2153818778","https://openalex.org/W2339428543","https://openalex.org/W2412925410","https://openalex.org/W2519493595","https://openalex.org/W2548791488","https://openalex.org/W2626015899","https://openalex.org/W2751033422","https://openalex.org/W2765739551","https://openalex.org/W2962947361","https://openalex.org/W6745515572"],"related_works":["https://openalex.org/W2124952510","https://openalex.org/W1502637513","https://openalex.org/W2013199662","https://openalex.org/W2375311607","https://openalex.org/W1930929277","https://openalex.org/W2163677711","https://openalex.org/W2036727360","https://openalex.org/W2158394102","https://openalex.org/W2240559849","https://openalex.org/W2011962637"],"abstract_inverted_index":{"Along":[0],"with":[1,47],"very":[2],"high-resolution":[3],"satellites":[4],"were":[5],"launched":[6],"frequently,":[7],"such":[8],"as":[9],"the":[10,61,102,108,116,122,141,144],"satellite":[11],"WorldView-3,":[12],"panchromatic":[13,39,69,87],"and":[14,28,33,86,127],"multispectral":[15,83],"remote-sensing":[16],"images":[17],"can":[18],"be":[19],"acquired":[20],"easily.":[21],"However,":[22],"it":[23],"is":[24,64,79,96],"still":[25],"an":[26,74,97],"interesting":[27],"challenging":[29],"task":[30],"to":[31,107],"fuse":[32],"classify":[34],"these":[35],"images.":[36],"In":[37,71],"general,":[38],"image":[40,53,85,89],"has":[41,55],"a":[42],"high":[43],"spatial":[44,62],"resolution,":[45],"but":[46,60],"only":[48],"one":[49],"spectral":[50],"band.":[51],"Multispectral":[52],"usually":[54],"four":[56,65],"or":[57],"eight":[58],"bands,":[59],"resolution":[63],"times":[66],"smaller":[67],"than":[68],"image.":[70],"this":[72],"paper,":[73],"unsupervised":[75],"feature":[76],"extraction":[77],"framework":[78],"proposed,":[80],"which":[81],"combines":[82],"(MS)":[84],"(PAN)":[88],"into":[90],"convolution":[91],"neural":[92],"network":[93],"(CNN).":[94],"There":[95],"image-to-image":[98],"mapping,":[99],"learning":[100],"from":[101],"input":[103],"source":[104,110],"(i.e.,":[105,111],"MS)":[106],"output":[109],"PAN).":[112],"Then,":[113],"by":[114],"integrating":[115],"hidden":[117],"layer":[118],"of":[119,133,143],"deep":[120],"CNN,":[121],"extracted":[123],"features":[124],"represent":[125],"MS":[126],"PAN":[128],"data.":[129],"The":[130],"experimental":[131],"results":[132],"two":[134],"practical":[135],"remote":[136],"sensing":[137],"data":[138],"sets":[139],"show":[140],"validity":[142],"framework.":[145]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}