{"id":"https://openalex.org/W3047443805","doi":"https://doi.org/10.1109/tgrs.2020.3015157","title":"Graph Convolutional Networks for Hyperspectral Image Classification","display_name":"Graph Convolutional Networks for Hyperspectral Image Classification","publication_year":2020,"publication_date":"2020-08-18","ids":{"openalex":"https://openalex.org/W3047443805","doi":"https://doi.org/10.1109/tgrs.2020.3015157","mag":"3047443805"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2020.3015157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3015157","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2008.02457","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5075013625","display_name":"Danfeng Hong","orcid":"https://orcid.org/0000-0002-3212-9584"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Danfeng Hong","raw_affiliation_strings":["Universit\u00e9. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-laboratory, Grenoble, France","GIPSA-SIGMAPHY - GIPSA - Signal Images Physique (GIPSA-lab, 11 rue des Math\u00e9matiques, Grenoble Campus BP46, F-38402 SAINT MARTIN D'HERES CEDEX - France)"],"raw_orcid":"https://orcid.org/0000-0002-3212-9584","affiliations":[{"raw_affiliation_string":"Universit\u00e9. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-laboratory, Grenoble, France","institution_ids":["https://openalex.org/I899635006","https://openalex.org/I1294671590","https://openalex.org/I106785703"]},{"raw_affiliation_string":"GIPSA-SIGMAPHY - GIPSA - Signal Images Physique (GIPSA-lab, 11 rue des Math\u00e9matiques, Grenoble Campus BP46, F-38402 SAINT MARTIN D'HERES CEDEX - France)","institution_ids":["https://openalex.org/I4210124956"]}]},{"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/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lianru Gao","raw_affiliation_strings":["Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","CAS - Chinese Academy of Sciences [Beijing] (52 Sanlihe Rd., Beijing, 100864 - China)"],"raw_orcid":"https://orcid.org/0000-0003-3888-8124","affiliations":[{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"CAS - Chinese Academy of Sciences [Beijing] (52 Sanlihe Rd., Beijing, 100864 - China)","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013885739","display_name":"Jing Yao","orcid":"https://orcid.org/0000-0003-1301-9758"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yao","raw_affiliation_strings":["School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an, China","Xjtu - Xi'an Jiaotong University (28 Xianning W Rd, JiaoDa ShangYe JieQu, Beilin Qu, Xian Shi, Shaanxi Sheng - China)"],"raw_orcid":"https://orcid.org/0000-0003-1301-9758","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi\u2019an Jiaotong University, Xi\u2019an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"Xjtu - Xi'an Jiaotong University (28 Xianning W Rd, JiaoDa ShangYe JieQu, Beilin Qu, Xian Shi, Shaanxi Sheng - China)","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100389658","display_name":"Bing Zhang","orcid":"https://orcid.org/0000-0001-7311-9844"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Zhang","raw_affiliation_strings":["College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China","Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","UCAS - University of Chinese Academy of Sciences [Beijing] (No.19(A) Yuquan Road, Shijingshan District, Beijing, P.R.China 100049 - China)","CAS - Chinese Academy of Sciences [Beijing] (52 Sanlihe Rd., Beijing, 100864 - China)"],"raw_orcid":"https://orcid.org/0000-0001-7311-9844","affiliations":[{"raw_affiliation_string":"College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"UCAS - University of Chinese Academy of Sciences [Beijing] (No.19(A) Yuquan Road, Shijingshan District, Beijing, P.R.China 100049 - China)","institution_ids":["https://openalex.org/I4210165038"]},{"raw_affiliation_string":"CAS - Chinese Academy of Sciences [Beijing] (52 Sanlihe Rd., Beijing, 100864 - China)","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054292278","display_name":"Antonio Plaza","orcid":"https://orcid.org/0000-0002-9613-1659"},"institutions":[{"id":"https://openalex.org/I80606768","display_name":"Universidad de Extremadura","ror":"https://ror.org/0174shg90","country_code":"ES","type":"education","lineage":["https://openalex.org/I80606768"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antonio Plaza","raw_affiliation_strings":["Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","UEX - Universidad de Extremadura - University of Extremadura (Badajoz\r\nC\u00e1ceres\r\nM\u00e9rida\r\nPlasencia - Spain)"],"raw_orcid":"https://orcid.org/0000-0002-9613-1659","affiliations":[{"raw_affiliation_string":"Hyperspectral Computing Laboratory, Escuela Polit\u00e9cnica, University of Extremadura, C\u00e1ceres, Spain","institution_ids":["https://openalex.org/I80606768"]},{"raw_affiliation_string":"UEX - Universidad de Extremadura - University of Extremadura (Badajoz\r\nC\u00e1ceres\r\nM\u00e9rida\r\nPlasencia - Spain)","institution_ids":["https://openalex.org/I80606768"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106124934","display_name":"Jocelyn Chanussot","orcid":"https://orcid.org/0000-0003-4817-2875"},"institutions":[{"id":"https://openalex.org/I106785703","display_name":"Institut polytechnique de Grenoble","ror":"https://ror.org/05sbt2524","country_code":"FR","type":"education","lineage":["https://openalex.org/I106785703","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I1294671590","display_name":"Centre National de la Recherche Scientifique","ror":"https://ror.org/02feahw73","country_code":"FR","type":"government","lineage":["https://openalex.org/I1294671590"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210124956","display_name":"GIPSA-Lab","ror":"https://ror.org/02wrme198","country_code":"FR","type":"facility","lineage":["https://openalex.org/I106785703","https://openalex.org/I1294671590","https://openalex.org/I4210124956","https://openalex.org/I899635006","https://openalex.org/I899635006"]},{"id":"https://openalex.org/I4210137199","display_name":"Aerospace Information Research Institute","ror":"https://ror.org/0419fj215","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210137199"]},{"id":"https://openalex.org/I899635006","display_name":"Universit\u00e9 Grenoble Alpes","ror":"https://ror.org/02rx3b187","country_code":"FR","type":"education","lineage":["https://openalex.org/I899635006"]}],"countries":["CN","FR"],"is_corresponding":false,"raw_author_name":"Jocelyn Chanussot","raw_affiliation_strings":["Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","Universit\u00e9. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-laboratory, Grenoble, France","GIPSA-SIGMAPHY - GIPSA - Signal Images Physique (GIPSA-lab, 11 rue des Math\u00e9matiques, Grenoble Campus BP46, F-38402 SAINT MARTIN D'HERES CEDEX - France)","CAS - Chinese Academy of Sciences [Beijing] (52 Sanlihe Rd., Beijing, 100864 - China)"],"raw_orcid":"https://orcid.org/0000-0003-4817-2875","affiliations":[{"raw_affiliation_string":"Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210137199","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Universit\u00e9. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-laboratory, Grenoble, France","institution_ids":["https://openalex.org/I899635006","https://openalex.org/I1294671590","https://openalex.org/I106785703"]},{"raw_affiliation_string":"GIPSA-SIGMAPHY - GIPSA - Signal Images Physique (GIPSA-lab, 11 rue des Math\u00e9matiques, Grenoble Campus BP46, F-38402 SAINT MARTIN D'HERES CEDEX - France)","institution_ids":["https://openalex.org/I4210124956"]},{"raw_affiliation_string":"CAS - Chinese Academy of Sciences [Beijing] (52 Sanlihe Rd., Beijing, 100864 - China)","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":117.2916,"has_fulltext":false,"cited_by_count":1650,"citation_normalized_percentile":{"value":0.99991932,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"59","issue":"7","first_page":"5966","last_page":"5978"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":1.0,"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":1.0,"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":0.9840999841690063,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9415000081062317,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"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/computer-science","display_name":"Computer science","score":0.7774776220321655},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6822124123573303},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.6274417042732239},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5815722942352295},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5790433883666992},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5735783576965332},{"id":"https://openalex.org/keywords/adjacency-matrix","display_name":"Adjacency matrix","score":0.5401550531387329},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49185681343078613},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.42492321133613586},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3928264379501343},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11411136388778687},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.09667879343032837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7774776220321655},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6822124123573303},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.6274417042732239},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5815722942352295},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5790433883666992},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5735783576965332},{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.5401550531387329},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49185681343078613},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.42492321133613586},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3928264379501343},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11411136388778687},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.09667879343032837},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tgrs.2020.3015157","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2020.3015157","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2008.02457","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.02457","pdf_url":"https://arxiv.org/pdf/2008.02457","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:HAL:hal-03429666v1","is_oa":true,"landing_page_url":"https://hal.science/hal-03429666","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ieeexplore.ieee.org/document/9170817","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2008.02457","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.02457","pdf_url":"https://arxiv.org/pdf/2008.02457","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1041279674","display_name":"MIAI @ Grenoble Alpes","funder_award_id":"ANR-19-P3IA-0003","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"},{"id":"https://openalex.org/G3584013848","display_name":null,"funder_award_id":"41722108","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8898889987","display_name":null,"funder_award_id":"91638201","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321048","display_name":"AXA Research Fund","ror":"https://ror.org/02zxqxw53"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":65,"referenced_works":["https://openalex.org/W1508936657","https://openalex.org/W1522301498","https://openalex.org/W1536340909","https://openalex.org/W1578099820","https://openalex.org/W1836465849","https://openalex.org/W1970406594","https://openalex.org/W2029316659","https://openalex.org/W2043665634","https://openalex.org/W2097915756","https://openalex.org/W2114819256","https://openalex.org/W2127199143","https://openalex.org/W2158787690","https://openalex.org/W2163886442","https://openalex.org/W2500751094","https://openalex.org/W2519887557","https://openalex.org/W2588117332","https://openalex.org/W2600746131","https://openalex.org/W2602024454","https://openalex.org/W2609880332","https://openalex.org/W2753248899","https://openalex.org/W2755992512","https://openalex.org/W2782517596","https://openalex.org/W2803057685","https://openalex.org/W2889773939","https://openalex.org/W2892621946","https://openalex.org/W2902746003","https://openalex.org/W2907147407","https://openalex.org/W2920405132","https://openalex.org/W2937675449","https://openalex.org/W2942454403","https://openalex.org/W2949117887","https://openalex.org/W2952565170","https://openalex.org/W2953308875","https://openalex.org/W2961295589","https://openalex.org/W2964015378","https://openalex.org/W2964121744","https://openalex.org/W2965945478","https://openalex.org/W2969881582","https://openalex.org/W2975089237","https://openalex.org/W2977355106","https://openalex.org/W2994639710","https://openalex.org/W2994968268","https://openalex.org/W3009883650","https://openalex.org/W3028306149","https://openalex.org/W3036200672","https://openalex.org/W3037458146","https://openalex.org/W3040988483","https://openalex.org/W3046027728","https://openalex.org/W3097170121","https://openalex.org/W3100011500","https://openalex.org/W3101012758","https://openalex.org/W3101640299","https://openalex.org/W3104313739","https://openalex.org/W3105021316","https://openalex.org/W3105298104","https://openalex.org/W3122774149","https://openalex.org/W3211952227","https://openalex.org/W4249991499","https://openalex.org/W4320339642","https://openalex.org/W6631190155","https://openalex.org/W6638667902","https://openalex.org/W6642674909","https://openalex.org/W6726873649","https://openalex.org/W6765543928","https://openalex.org/W6768889568"],"related_works":["https://openalex.org/W2595172197","https://openalex.org/W2373577936","https://openalex.org/W2072166414","https://openalex.org/W2084856301","https://openalex.org/W2127970246","https://openalex.org/W2885125400","https://openalex.org/W1989889224","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3095575180"],"abstract_inverted_index":{"Convolutional":[0],"neural":[1],"networks":[2,42,139],"(CNNs)":[3],"have":[4,44],"been":[5,45],"attracting":[6],"increasing":[7],"attention":[8],"in":[9,26,51,71,99,123],"hyperspectral":[10],"(HS)":[11],"image":[12,75],"classification":[13,142],"due":[14],"to":[15,18,78,119,159,169,199,230],"their":[16,24],"ability":[17,25],"capture":[19],"spatial-spectral":[20],"feature":[21],"representations.":[22],"Nevertheless,":[23],"modeling":[27],"relations":[28],"between":[29],"the":[30,35,79,82,87,161,180,201,214,221,224,231,248],"samples":[31],"remains":[32],"limited.":[33],"Beyond":[34],"limitations":[36],"of":[37,73,81,133,153,164,182,216,223,239,250],"grid":[38],"sampling,":[39],"graph":[40],"convolutional":[41],"(GCNs)":[43],"recently":[46],"proposed":[47],"and":[48,57,66,69,140,147,184,196,220],"successfully":[49],"applied":[50],"irregular":[52],"(or":[53],"nongrid)":[54],"data":[55,136,211],"representation":[56],"analysis.":[58],"In":[59],"this":[60,106,240],"article,":[61],"we":[62,108,186],"thoroughly":[63],"investigate":[64],"CNNs":[65,146,183],"GCNs":[67,90,122,148,219],"(qualitatively":[68],"quantitatively)":[70],"terms":[72],"HS":[74,154,210],"classification.":[76],"Due":[77],"construction":[80],"adjacency":[83],"matrix":[84],"on":[85,208],"all":[86],"data,":[88],"traditional":[89],"usually":[91],"suffer":[92],"from":[93],"a":[94,110,124,165],"huge":[95],"computational":[96],"cost,":[97],"particularly":[98],"large-scale":[100,121],"remote":[101],"sensing":[102],"(RS)":[103],"problems.":[104],"To":[105],"end,":[107],"develop":[109],"new":[111],"minibatch":[112,125],"GCN":[113,235],"(called":[114],"miniGCN":[115,130],"hereinafter),":[116],"which":[117],"allows":[118],"train":[120],"fashion.":[126],"More":[127],"significantly,":[128],"our":[129],"is":[131,168],"capable":[132],"inferring":[134],"out-of-sample":[135],"without":[137],"retraining":[138],"improving":[141],"performance.":[143],"Furthermore,":[144],"as":[145],"can":[149,174],"extract":[150],"different":[151],"types":[152],"features,":[155],"an":[156],"intuitive":[157],"solution":[158],"break":[160],"performance":[162,203],"bottleneck":[163],"single":[166,232],"model":[167],"fuse":[170],"them.":[171],"Since":[172],"miniGCNs":[173,217],"perform":[175],"batchwise":[176],"network":[177],"training":[178],"(enabling":[179],"combination":[181],"GCNs),":[185],"explore":[187],"three":[188,209],"fusion":[189,198,226],"strategies:":[190],"additive":[191],"fusion,":[192,195],"elementwise":[193],"multiplicative":[194],"concatenation":[197],"measure":[200],"obtained":[202],"gain.":[204],"Extensive":[205],"experiments,":[206],"conducted":[207],"sets,":[212],"demonstrate":[213],"advantages":[215],"over":[218],"superiority":[222],"tested":[225],"strategies":[227],"with":[228],"regard":[229],"CNN":[233],"or":[234],"models.":[236],"The":[237],"codes":[238],"work":[241],"will":[242],"be":[243],"available":[244],"at":[245],"https://github.com/danfenghong/IEEE_TGRS_GCN":[246],"for":[247],"sake":[249],"reproducibility.":[251]},"counts_by_year":[{"year":2026,"cited_by_count":70},{"year":2025,"cited_by_count":227},{"year":2024,"cited_by_count":298},{"year":2023,"cited_by_count":415},{"year":2022,"cited_by_count":339},{"year":2021,"cited_by_count":268},{"year":2020,"cited_by_count":33}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}
