{"id":"https://openalex.org/W2900672554","doi":"https://doi.org/10.1109/igarss.2018.8518292","title":"Hyperspectral Classification Via Spatial Context Exploration with Multi-Scale CNN","display_name":"Hyperspectral Classification Via Spatial Context Exploration with Multi-Scale CNN","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2900672554","doi":"https://doi.org/10.1109/igarss.2018.8518292","mag":"2900672554"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2018.8518292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518292","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/A5006192981","display_name":"Zhongqi Tian","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongqi Tian","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022330186","display_name":"Jingyu Ji","orcid":"https://orcid.org/0000-0001-6806-7437"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyu Ji","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067207818","display_name":"Shaohui Mei","orcid":"https://orcid.org/0000-0002-8018-596X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohui Mei","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031957432","display_name":"Junhui Hou","orcid":"https://orcid.org/0000-0003-3431-2021"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Junhui Hou","raw_affiliation_strings":["Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055653807","display_name":"Shuai Wan","orcid":"https://orcid.org/0000-0001-8617-149X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Wan","raw_affiliation_strings":["School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Northwestern Polytechnical University, Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"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, MS, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5006192981"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":1.6457,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.87341551,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"9","issue":null,"first_page":"2563","last_page":"2566"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9954000115394592,"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"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9596999883651733,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8840850591659546},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.7945455312728882},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7325712442398071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7219356298446655},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7175529599189758},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.703294038772583},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.6808141469955444},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6422125101089478},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.569952666759491},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5676236748695374},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4859865605831146},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4702566862106323},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.445323646068573},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.42606014013290405},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4157858192920685},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3905450701713562},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.30147111415863037},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.27719125151634216},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1984216272830963},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08103930950164795},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.059483110904693604}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8840850591659546},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.7945455312728882},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7325712442398071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7219356298446655},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7175529599189758},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.703294038772583},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.6808141469955444},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6422125101089478},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.569952666759491},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5676236748695374},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4859865605831146},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4702566862106323},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.445323646068573},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.42606014013290405},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4157858192920685},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3905450701713562},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.30147111415863037},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.27719125151634216},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1984216272830963},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08103930950164795},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.059483110904693604},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2018.8518292","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2018.8518292","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1521436688","https://openalex.org/W1966580635","https://openalex.org/W2130939260","https://openalex.org/W2500751094","https://openalex.org/W2548791488","https://openalex.org/W2572303978","https://openalex.org/W2611655888","https://openalex.org/W2780885700"],"related_works":["https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2579567122","https://openalex.org/W3148227991","https://openalex.org/W1486593826","https://openalex.org/W2771174107","https://openalex.org/W1536965844","https://openalex.org/W2344941099","https://openalex.org/W4322212724"],"abstract_inverted_index":{"Spatial":[0],"context":[1,23,46,64,85,122],"has":[2],"shown":[3],"to":[4,41,60,77,119],"be":[5,39],"very":[6],"useful":[7],"in":[8,28,47,65,68],"hyperspectral":[9,19,49,142],"image":[10],"processing.":[11],"Existing":[12],"convolutional":[13],"neural":[14],"network":[15],"(CNN)-based":[16],"methods":[17],"for":[18,100,139],"classification":[20,140],"explore":[21,42,61,120],"spatial":[22,45,63,71,84,93,113,121,126],"by":[24,91],"single-scale":[25,35,125],"convolution":[26,36,73,115,127],"kernels":[27,74,94],"2D":[29],"or":[30],"3D":[31],"shapes.":[32],"However,":[33],"such":[34],"may":[37],"not":[38],"capable":[40],"the":[43,62,110,129,132],"complex":[44],"a":[48,56],"image.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54],"propose":[55],"multi-scale":[57],"CNN,":[58],"MS-CNN":[59,134],"different":[66,92],"extents,":[67],"which":[69],"adaptive":[70,112],"neighborhood":[72,114],"are":[75,95,116],"used":[76],"simultaneously":[78],"extract":[79],"multiple":[80],"spectral-spatial":[81],"features":[82,89],"from":[83],"of":[86,131,141],"pixels.":[87],"These":[88],"obtained":[90],"then":[96],"concatenated":[97],"and":[98,104,128],"fused":[99],"further":[101],"feature":[102],"extraction":[103],"classification.":[105],"Experimental":[106],"results":[107],"show":[108],"that":[109],"proposed":[111,133],"more":[117],"effective":[118],"than":[123],"traditional":[124],"performance":[130],"outperforms":[135],"several":[136],"state-of-art":[137],"CNNs":[138],"images.":[143]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
