{"id":"https://openalex.org/W4382176353","doi":"https://doi.org/10.1080/17538947.2023.2210310","title":"GACP: graph neural networks with ARMA filters and a parallel CNN for hyperspectral image classification","display_name":"GACP: graph neural networks with ARMA filters and a parallel CNN for hyperspectral image classification","publication_year":2023,"publication_date":"2023-05-15","ids":{"openalex":"https://openalex.org/W4382176353","doi":"https://doi.org/10.1080/17538947.2023.2210310"},"language":"en","primary_location":{"id":"doi:10.1080/17538947.2023.2210310","is_oa":true,"landing_page_url":"https://doi.org/10.1080/17538947.2023.2210310","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2210310?needAccess=true&role=button","source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Digital Earth","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2210310?needAccess=true&role=button","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074326967","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0003-1915-9487"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yang","raw_affiliation_strings":["School of Mechanical Engineering, Guizhou University, Guiyang, People\u2019s Republic of China","State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People\u2019s Republic of China","School of Mechanical Engineering, Guizhou University, Guiyang, People's Republic of China","State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0003-1915-9487","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Guizhou University, Guiyang, People\u2019s Republic of China","institution_ids":["https://openalex.org/I178232147"]},{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People\u2019s Republic of China","institution_ids":["https://openalex.org/I178232147"]},{"raw_affiliation_string":"School of Mechanical Engineering, Guizhou University, Guiyang, People's Republic of China","institution_ids":["https://openalex.org/I178232147"]},{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People's Republic of China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045865265","display_name":"Jie Sun","orcid":"https://orcid.org/0000-0002-1162-1676"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Sun","raw_affiliation_strings":["School of Mechanical Engineering, Guizhou University, Guiyang, People\u2019s Republic of China","School of Mechanical Engineering, Guizhou University, Guiyang, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0002-1162-1676","affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Guizhou University, Guiyang, People\u2019s Republic of China","institution_ids":["https://openalex.org/I178232147"]},{"raw_affiliation_string":"School of Mechanical Engineering, Guizhou University, Guiyang, People's Republic of China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010687103","display_name":"Yaping Ren","orcid":"https://orcid.org/0000-0002-2411-9853"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaping Ren","raw_affiliation_strings":["School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai, People\u2019s Republic of China","School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0002-2411-9853","affiliations":[{"raw_affiliation_string":"School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai, People\u2019s Republic of China","institution_ids":["https://openalex.org/I159948400"]},{"raw_affiliation_string":"School of Intelligent Systems Science and Engineering, Jinan University, Zhuhai, People's Republic of China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100354322","display_name":"Shaobo Li","orcid":"https://orcid.org/0000-0003-4759-6000"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaobo Li","raw_affiliation_strings":["State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People\u2019s Republic of China","State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0003-4759-6000","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People\u2019s Republic of China","institution_ids":["https://openalex.org/I178232147"]},{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People's Republic of China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102994375","display_name":"Shujie Ding","orcid":"https://orcid.org/0000-0001-6160-5765"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shujie Ding","raw_affiliation_strings":["State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People\u2019s Republic of China","State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People's Republic of China"],"raw_orcid":"https://orcid.org/0000-0001-6160-5765","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People\u2019s Republic of China","institution_ids":["https://openalex.org/I178232147"]},{"raw_affiliation_string":"State Key Laboratory of Public Big Data, Guizhou University, Guiyang, People's Republic of China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060537711","display_name":"Jianjun Hu","orcid":"https://orcid.org/0000-0002-8725-6660"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianjun Hu","raw_affiliation_strings":["Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA"],"raw_orcid":"https://orcid.org/0000-0002-8725-6660","affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of South Carolina, Columbia, SC, USA","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5045865265"],"corresponding_institution_ids":["https://openalex.org/I178232147"],"apc_list":{"value":2390,"currency":"USD","value_usd":2390},"apc_paid":{"value":2390,"currency":"USD","value_usd":2390},"fwci":1.5006,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.8295006,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"16","issue":"1","first_page":"1770","last_page":"1800"},"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":0.993399977684021,"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9506000280380249,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.8241045475006104},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6149031519889832},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5798820853233337},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5724636912345886},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5570272207260132},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5320749282836914},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.48002973198890686},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.45913106203079224},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4503277540206909},{"id":"https://openalex.org/keywords/spectral-signature","display_name":"Spectral signature","score":0.44225043058395386},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.43878495693206787},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.43090540170669556},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3443984389305115},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14864298701286316},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.12754973769187927},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09627848863601685}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8241045475006104},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6149031519889832},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5798820853233337},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5724636912345886},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5570272207260132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5320749282836914},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.48002973198890686},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.45913106203079224},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4503277540206909},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.44225043058395386},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.43878495693206787},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.43090540170669556},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3443984389305115},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14864298701286316},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.12754973769187927},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09627848863601685}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1080/17538947.2023.2210310","is_oa":true,"landing_page_url":"https://doi.org/10.1080/17538947.2023.2210310","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2210310?needAccess=true&role=button","source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Digital Earth","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ac4c8b49193d468fac796368d08c1e3b","is_oa":true,"landing_page_url":"https://doaj.org/article/ac4c8b49193d468fac796368d08c1e3b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"International Journal of Digital Earth, Vol 16, Iss 1, Pp 1770-1800 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1080/17538947.2023.2210310","is_oa":true,"landing_page_url":"https://doi.org/10.1080/17538947.2023.2210310","pdf_url":"https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2210310?needAccess=true&role=button","source":{"id":"https://openalex.org/S199162493","display_name":"International Journal of Digital Earth","issn_l":"1753-8947","issn":["1753-8947","1753-8955"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Digital Earth","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.8399999737739563}],"awards":[{"id":"https://openalex.org/G6279372052","display_name":null,"funder_award_id":"2018AAA0101800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G6360692046","display_name":null,"funder_award_id":"62166005","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/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4382176353.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W2737996023","https://openalex.org/W2764276316","https://openalex.org/W2772452219","https://openalex.org/W2808098982","https://openalex.org/W2912636151","https://openalex.org/W2914331134","https://openalex.org/W2964015378","https://openalex.org/W2972056571","https://openalex.org/W3043248362","https://openalex.org/W3049655825","https://openalex.org/W3093730405","https://openalex.org/W3105357426","https://openalex.org/W3107591966","https://openalex.org/W3111390112","https://openalex.org/W3112488517","https://openalex.org/W3113552858","https://openalex.org/W3119997721","https://openalex.org/W3120948300","https://openalex.org/W3128530330","https://openalex.org/W3128547190","https://openalex.org/W3132896347","https://openalex.org/W3133954504","https://openalex.org/W3134136658","https://openalex.org/W3138725786","https://openalex.org/W3149380949","https://openalex.org/W3155362250","https://openalex.org/W3177994465","https://openalex.org/W3178246703","https://openalex.org/W3192524834","https://openalex.org/W3196410189","https://openalex.org/W3198862639","https://openalex.org/W3201461236","https://openalex.org/W3211938211","https://openalex.org/W3212737115","https://openalex.org/W4200482478","https://openalex.org/W4206065110","https://openalex.org/W4210541032","https://openalex.org/W4213235909","https://openalex.org/W4226070402","https://openalex.org/W4281566243","https://openalex.org/W4283370550","https://openalex.org/W4283760989","https://openalex.org/W4285091973","https://openalex.org/W4296425803","https://openalex.org/W4297733535","https://openalex.org/W4313525856"],"related_works":["https://openalex.org/W2738168532","https://openalex.org/W4367471608","https://openalex.org/W2037328426","https://openalex.org/W2054439167","https://openalex.org/W2889956472","https://openalex.org/W2044594927","https://openalex.org/W2791078257","https://openalex.org/W2539574252","https://openalex.org/W2012636591","https://openalex.org/W4244482010"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"the":[3,48,71,89,93,100,104,112,120,144,148,156,163,171,179],"use":[4],"of":[5,50,55,62,67,147,195],"convolutional":[6],"neural":[7,12],"networks":[8,13],"(CNNs)":[9],"and":[10,24,36,97,134,170],"graph":[11],"(GNNs)":[14],"to":[15,142],"identify":[16],"hyperspectral":[17],"images":[18],"(HSIs)":[19],"has":[20],"achieved":[21],"excellent":[22],"results,":[23],"such":[25],"methods":[26],"are":[27,45,137],"widely":[28,157],"used":[29,158],"in":[30,70,92],"agricultural":[31],"remote":[32,38],"sensing,":[33],"geological":[34],"exploration,":[35],"marine":[37],"sensing.":[39],"Although":[40],"many":[41],"generalization":[42],"classification":[43,185],"algorithms":[44],"designed":[46],"for":[47,150],"purpose":[49],"learning":[51,145],"a":[52,60,63,78,125,192],"small":[53,193],"number":[54,194],"samples,":[56],"there":[57],"is":[58,122],"often":[59],"problem":[61],"low":[64],"utilization":[65],"rate":[66],"position":[68,116],"information":[69,91,102,117],"empty":[72],"spectral":[73,95,114],"domain.":[74],"Based":[75],"on":[76,155],"this,":[77],"GNN":[79],"with":[80,187,191],"an":[81],"autoregressive":[82],"moving":[83],"average":[84],"(ARMA)-based":[85],"smoothing":[86],"filter":[87],"samples":[88],"node":[90],"null":[94,113],"domain":[96,115],"then":[98],"captures":[99],"spatial":[101,108,132],"at":[103],"pixel":[105],"level":[106],"via":[107],"feature":[109],"convolution;":[110],"then,":[111],"lost":[118],"by":[119,124],"CNN":[121],"located":[123],"coordinate":[126],"attention":[127],"(CA)":[128],"mechanism.":[129],"Finally,":[130],"autoregressive,":[131],"convolution,":[133],"CA":[135],"mechanisms":[136],"combined":[138],"into":[139],"multiscale":[140],"features":[141],"enhance":[143],"capacity":[146],"network":[149],"tiny":[151],"samples.":[152],"Experiments":[153],"conducted":[154],"Indian":[159],"Pines":[160],"(IP)":[161],"dataset,":[162,166],"Botswana":[164],"(BS)":[165],"Houton":[167],"2013":[168],"(H2013),":[169],"WHU-Hi-HongHu":[172],"(WHU)":[173],"benchmark":[174],"HSI":[175],"dataset":[176],"demonstrate":[177],"that":[178],"proposed":[180],"GACP":[181],"technique":[182],"can":[183],"perform":[184],"work":[186],"good":[188],"accuracy":[189],"even":[190],"training":[196],"examples.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
