{"id":"https://openalex.org/W2890133123","doi":"https://doi.org/10.1109/tcyb.2018.2864670","title":"Feature Extraction for Classification of Hyperspectral and LiDAR Data Using Patch-to-Patch CNN","display_name":"Feature Extraction for Classification of Hyperspectral and LiDAR Data Using Patch-to-Patch CNN","publication_year":2018,"publication_date":"2018-09-18","ids":{"openalex":"https://openalex.org/W2890133123","doi":"https://doi.org/10.1109/tcyb.2018.2864670","mag":"2890133123","pmid":"https://pubmed.ncbi.nlm.nih.gov/30235156"},"language":"en","primary_location":{"id":"doi:10.1109/tcyb.2018.2864670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2018.2864670","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/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 and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5724-9785","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","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 and Technology, Beijing University of Chemical Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7015-7335","affiliations":[{"raw_affiliation_string":"College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China","institution_ids":["https://openalex.org/I75390827"]}]},{"author_position":"middle","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, Starkville, MS, USA"],"raw_orcid":"https://orcid.org/0000-0001-8354-7500","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS, USA","institution_ids":["https://openalex.org/I99041443"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066378186","display_name":"Lianru Gao","orcid":"https://orcid.org/0000-0003-3888-8124"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianru Gao","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-3888-8124","affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100389658","display_name":"Bing Zhang","orcid":"https://orcid.org/0000-0001-7311-9844"},"institutions":[{"id":"https://openalex.org/I4210128053","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128053"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Zhang","raw_affiliation_strings":["Institute of Remote Sensing and Digital Earth, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Remote Sensing and Digital Earth, Beijing, China","institution_ids":["https://openalex.org/I4210128053"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.98,"has_fulltext":false,"cited_by_count":287,"citation_normalized_percentile":{"value":0.99224539,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"50","issue":"1","first_page":"100","last_page":"111"},"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":0.9958000183105469,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9918000102043152,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/lidar","display_name":"Lidar","score":0.8136917948722839},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7590100169181824},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.7126237154006958},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6378173828125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6350947022438049},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6082725524902344},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5750712156295776},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5406507849693298},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5218921303749084},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5151230692863464},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47797366976737976},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.4736667275428772},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4195806086063385},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41168636083602905},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09032842516899109}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8136917948722839},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7590100169181824},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7126237154006958},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6378173828125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6350947022438049},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6082725524902344},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5750712156295776},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5406507849693298},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5218921303749084},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5151230692863464},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47797366976737976},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.4736667275428772},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4195806086063385},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41168636083602905},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09032842516899109},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tcyb.2018.2864670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tcyb.2018.2864670","pdf_url":null,"source":{"id":"https://openalex.org/S4210191041","display_name":"IEEE Transactions on Cybernetics","issn_l":"2168-2267","issn":["2168-2267","2168-2275"],"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 Transactions on Cybernetics","raw_type":"journal-article"},{"id":"pmid:30235156","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30235156","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on cybernetics","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.5400000214576721}],"awards":[{"id":"https://openalex.org/G1146082295","display_name":null,"funder_award_id":"4172043","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"},{"id":"https://openalex.org/G1545149281","display_name":null,"funder_award_id":"NSFC-91638201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2043223440","display_name":null,"funder_award_id":"BUCTRC201615","funder_id":"https://openalex.org/F4320321392","funder_display_name":"Northwestern Polytechnical University"},{"id":"https://openalex.org/G4015423121","display_name":null,"funder_award_id":"Z171100001117050","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"},{"id":"https://openalex.org/G6501339799","display_name":"\u8868\u793a\u6a21\u578b\u6846\u67b6\u4e0b\u9ad8\u5149\u8c31\u9065\u611f\u5f71\u50cf\u5206\u7c7b\u82e5\u5e72\u6280\u672f\u7814\u7a76","funder_award_id":"61571033","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"},{"id":"https://openalex.org/F4320321392","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"},{"id":"https://openalex.org/F4320336006","display_name":"Institute of Remote Sensing and Digital Earth","ror":"https://ror.org/02cjszf03"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1497089125","https://openalex.org/W1522301498","https://openalex.org/W1836465849","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2011085793","https://openalex.org/W2029316659","https://openalex.org/W2029992428","https://openalex.org/W2065407071","https://openalex.org/W2067874135","https://openalex.org/W2086866337","https://openalex.org/W2097117768","https://openalex.org/W2100495367","https://openalex.org/W2127152713","https://openalex.org/W2147800946","https://openalex.org/W2165796970","https://openalex.org/W2179290474","https://openalex.org/W2320738207","https://openalex.org/W2320846209","https://openalex.org/W2412588858","https://openalex.org/W2518815253","https://openalex.org/W2548791488","https://openalex.org/W2565258258","https://openalex.org/W2572303978","https://openalex.org/W2592141703","https://openalex.org/W2598997103","https://openalex.org/W2606929568","https://openalex.org/W2611655888","https://openalex.org/W2614256707","https://openalex.org/W2626015899","https://openalex.org/W2719511702","https://openalex.org/W2751033422","https://openalex.org/W2757208835","https://openalex.org/W2764205729","https://openalex.org/W2765739551","https://openalex.org/W2768537477","https://openalex.org/W2789643644","https://openalex.org/W2791928749","https://openalex.org/W2949117887","https://openalex.org/W2952430178","https://openalex.org/W2962947361","https://openalex.org/W2963446712","https://openalex.org/W2989855043","https://openalex.org/W3103753223","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6657934682","https://openalex.org/W6725739302","https://openalex.org/W6764653903"],"related_works":["https://openalex.org/W2783354812","https://openalex.org/W4384112194","https://openalex.org/W2103009189","https://openalex.org/W4312958259","https://openalex.org/W4308259661","https://openalex.org/W4390813131","https://openalex.org/W2349383066","https://openalex.org/W4328132048","https://openalex.org/W2594043982","https://openalex.org/W3036493597"],"abstract_inverted_index":{"Multisensor":[0],"fusion":[1],"is":[2,58,74],"of":[3,63,101,138],"great":[4],"importance":[5],"in":[6],"Earth":[7],"observation":[8],"related":[9],"applications.":[10],"For":[11],"instance,":[12],"hyperspectral":[13,64],"images":[14],"(HSIs)":[15],"provide":[16,27],"wealthy":[17],"spectral":[18],"information":[19],"while":[20],"light":[21],"detection":[22],"and":[23,30,33,65,127,174],"ranging":[24],"(LiDAR)":[25],"data":[26,35,151],"elevation":[28],"information,":[29],"using":[31],"HSI":[32,83],"LiDAR":[34,66,85],"together":[36],"can":[37],"achieve":[38],"better":[39],"classification":[40,62,141],"performance.":[41],"In":[42],"this":[43],"paper,":[44],"an":[45,79],"unsupervised":[46],"feature":[47],"extraction":[48],"framework,":[49,142],"named":[50],"as":[51,171],"patch-to-patch":[52],"convolutional":[53],"neural":[54],"network":[55],"(PToP":[56],"CNN),":[57],"proposed":[59,140,159],"for":[60],"collaborative":[61],"data.":[67],"More":[68],"specific,":[69],"a":[70,124],"three-tower":[71],"PToP":[72,104],"mapping":[73],"first":[75],"developed":[76],"to":[77,84,110],"seek":[78],"accurate":[80],"representation":[81],"from":[82,117],"data,":[86],"aiming":[87],"at":[88],"merging":[89],"multiscale":[90],"features":[91,107,116],"between":[92],"two":[93,147],"different":[94,118],"sources.":[95],"Then,":[96],"by":[97],"integrating":[98],"hidden":[99,119],"layers":[100,120],"the":[102,136,139,158],"designed":[103],"CNN,":[105],"extracted":[106],"are":[108,121,144],"expected":[109],"possess":[111],"deeply":[112],"fused":[113],"characteristics.":[114],"Accordingly,":[115],"concatenated":[122],"into":[123,129],"stacked":[125],"vector":[126],"fed":[128],"three":[130],"fully":[131],"connected":[132],"layers.":[133],"To":[134],"verify":[135],"effectiveness":[137],"experiments":[143],"executed":[145],"on":[146],"benchmark":[148],"remote":[149],"sensing":[150],"sets.":[152],"The":[153],"experimental":[154],"results":[155],"demonstrate":[156],"that":[157],"method":[160],"provides":[161],"superior":[162],"performance":[163],"when":[164],"compared":[165],"with":[166],"some":[167],"state-of-the-art":[168],"classifiers,":[169],"such":[170],"two-branch":[172],"CNN":[173],"context":[175],"CNN.":[176]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":37},{"year":2024,"cited_by_count":42},{"year":2023,"cited_by_count":35},{"year":2022,"cited_by_count":62},{"year":2021,"cited_by_count":62},{"year":2020,"cited_by_count":34},{"year":2019,"cited_by_count":6}],"updated_date":"2026-08-11T07:18:39.950985","created_date":"2025-10-10T00:00:00"}