{"id":"https://openalex.org/W4283260867","doi":"https://doi.org/10.1109/tnnls.2022.3182715","title":"Graph-in-Graph Convolutional Network for Hyperspectral Image Classification","display_name":"Graph-in-Graph Convolutional Network for Hyperspectral Image Classification","publication_year":2022,"publication_date":"2022-06-20","ids":{"openalex":"https://openalex.org/W4283260867","doi":"https://doi.org/10.1109/tnnls.2022.3182715","pmid":"https://pubmed.ncbi.nlm.nih.gov/35724277"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2022.3182715","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3182715","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","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/A5035753061","display_name":"Sen Jia","orcid":"https://orcid.org/0000-0001-9742-5037"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Sen Jia","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-9742-5037","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012282514","display_name":"Shuguo Jiang","orcid":"https://orcid.org/0009-0001-9850-1043"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuguo Jiang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037478762","display_name":"Shuyu Zhang","orcid":"https://orcid.org/0000-0003-2038-0349"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyu Zhang","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2038-0349","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I211433327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038002446","display_name":"Meng Xu","orcid":"https://orcid.org/0000-0002-4056-7787"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]},{"id":"https://openalex.org/I211433327","display_name":"Ministry of Natural Resources","ror":"https://ror.org/02kxqx159","country_code":"CN","type":"government","lineage":["https://openalex.org/I211433327","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Xu","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4056-7787","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]},{"raw_affiliation_string":"Key Laboratory for Geo-Environmental Monitoring of Coastal Zone, Ministry of Natural Resources, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961","https://openalex.org/I211433327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024631382","display_name":"Xiuping Jia","orcid":"https://orcid.org/0000-0001-9916-6382"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiuping Jia","raw_affiliation_strings":["School of Engineering and Information Technology, University of New South Wales, Canberra, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9916-6382","affiliations":[{"raw_affiliation_string":"School of Engineering and Information Technology, University of New South Wales, Canberra, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5035753061"],"corresponding_institution_ids":["https://openalex.org/I180726961","https://openalex.org/I211433327"],"apc_list":null,"apc_paid":null,"fwci":16.1656,"has_fulltext":false,"cited_by_count":154,"citation_normalized_percentile":{"value":0.99389417,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"35","issue":"1","first_page":"1157","last_page":"1171"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9930999875068665,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer 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":0.7355189919471741},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.582598865032196},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5204337239265442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5178823471069336},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46553483605384827},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14294728636741638}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7355189919471741},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.582598865032196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5204337239265442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5178823471069336},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46553483605384827},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14294728636741638}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2022.3182715","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2022.3182715","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:35724277","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35724277","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 neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2264764757","display_name":null,"funder_award_id":"61901278","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2721654555","display_name":null,"funder_award_id":"2022A1515011290","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G3638989402","display_name":null,"funder_award_id":"41971300","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5251528771","display_name":null,"funder_award_id":"20200803152531004","funder_id":"https://openalex.org/F4320329801","funder_display_name":"Shenzhen Research and Development Program"},{"id":"https://openalex.org/G6222615510","display_name":null,"funder_award_id":"2020ZDZX3045","funder_id":"https://openalex.org/F4320326279","funder_display_name":"Department of Education of Guangdong Province"},{"id":"https://openalex.org/G6376546062","display_name":null,"funder_award_id":"2021A1515011413","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320326279","display_name":"Department of Education of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320329801","display_name":"Shenzhen Research and Development Program","ror":null},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W1901129140","https://openalex.org/W1990914742","https://openalex.org/W1994168328","https://openalex.org/W2006280268","https://openalex.org/W2029316659","https://openalex.org/W2097117768","https://openalex.org/W2116699851","https://openalex.org/W2118246710","https://openalex.org/W2194187530","https://openalex.org/W2194775991","https://openalex.org/W2248124113","https://openalex.org/W2519653196","https://openalex.org/W2614326984","https://openalex.org/W2751748110","https://openalex.org/W2777427437","https://openalex.org/W2792724009","https://openalex.org/W2808979303","https://openalex.org/W2884367402","https://openalex.org/W2888715336","https://openalex.org/W2892621946","https://openalex.org/W2940678725","https://openalex.org/W2954497554","https://openalex.org/W2963037989","https://openalex.org/W2964015378","https://openalex.org/W2982217661","https://openalex.org/W2986799142","https://openalex.org/W2991494819","https://openalex.org/W3000978536","https://openalex.org/W3011095215","https://openalex.org/W3012399044","https://openalex.org/W3013868170","https://openalex.org/W3019166713","https://openalex.org/W3031696893","https://openalex.org/W3040575072","https://openalex.org/W3047443805","https://openalex.org/W3083068801","https://openalex.org/W3094570690","https://openalex.org/W3103695279","https://openalex.org/W3111727634","https://openalex.org/W3120358876","https://openalex.org/W3127131334","https://openalex.org/W3153805261","https://openalex.org/W3159459366","https://openalex.org/W3171239615","https://openalex.org/W3196001250","https://openalex.org/W3200799048","https://openalex.org/W3201461236","https://openalex.org/W4240485910","https://openalex.org/W6638444622","https://openalex.org/W6726873649","https://openalex.org/W6738964360","https://openalex.org/W6744179516","https://openalex.org/W6760001035"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"With":[0],"the":[1,99,130,140,149,176,187,198,202,206,210,241],"development":[2],"of":[3,53,104,156,178,189],"hyperspectral":[4,7],"sensors,":[5],"accessible":[6],"images":[8],"(HSIs)":[9],"are":[10,47,197],"increasing,":[11],"and":[12,34,73,93,101,158,169,209,229],"pixel-oriented":[13],"classification":[14,82,233],"has":[15],"attracted":[16],"much":[17],"attention.":[18],"Recently,":[19],"graph":[20,125,142,160],"convolutional":[21,77],"networks":[22],"(GCNs)":[23],"have":[24,35],"been":[25,36],"proposed":[26,68,225],"to":[27,49,57,98,118,129,165,184,200],"process":[28],"graph-structured":[29],"data":[30],"in":[31,38,64,139],"non-Euclidean":[32],"domains":[33],"employed":[37],"HSI":[39,81,110,214,232],"classification.":[40,215],"But":[41],"most":[42],"methods":[43],"based":[44],"on":[45,218],"GCN":[46],"hard":[48],"sufficiently":[50],"exploit":[51],"information":[52,91],"ground":[54,105],"objects":[55],"due":[56],"feature":[58],"aggregation.":[59],"To":[60],"solve":[61],"this":[62,65,245],"issue,":[63],"article,":[66],"we":[67,196],"a":[69,74,84,144],"graph-in-graph":[70],"(GiG)":[71],"model":[72],"related":[75],"GiG":[76,88,151,203],"network":[78],"(GiGCN)":[79],"for":[80,213,231,244],"from":[83,205],"superpixel":[85,207],"viewpoint.":[86],"The":[87],"representation":[89],"covers":[90],"inside":[92],"outside":[94],"superpixels,":[95,113],"respectively,":[96],"corresponding":[97,145],"local":[100],"global":[102],"characteristics":[103],"objects.":[106],"Concretely,":[107],"after":[108],"segmenting":[109],"into":[111,172],"disjoint":[112],"each":[114,137],"one":[115],"is":[116,126,163,182,192,227,247],"converted":[117],"an":[119,123],"internal":[120,146,157],"graph.":[121],"Meanwhile,":[122],"external":[124,141],"constructed":[127],"according":[128],"spatial":[131],"adjacent":[132],"relationships":[133],"among":[134],"superpixels.":[135],"Significantly,":[136],"node":[138],"embeds":[143],"graph,":[147],"forming":[148],"so-called":[150],"structure.":[152],"Then,":[153],"GiGCN":[154,211],"composed":[155],"External":[159],"convolution":[161],"(EGC)":[162],"designed":[164],"extract":[166],"hierarchical":[167],"features":[168],"integrate":[170],"them":[171],"multiple":[173],"scales,":[174],"improving":[175],"discriminability":[177],"GiGCN.":[179,190],"Ensemble":[180],"learning":[181],"incorporated":[183],"further":[185],"boost":[186],"robustness":[188],"It":[191],"worth":[193],"noting":[194],"that":[195,223],"first":[199],"propose":[201],"framework":[204],"point":[208],"scheme":[212],"Experiment":[216],"results":[217],"four":[219],"benchmark":[220],"datasets":[221],"demonstrate":[222],"our":[224],"method":[226],"effective":[228],"feasible":[230],"with":[234],"limited":[235],"labeled":[236],"samples.":[237],"For":[238],"study":[239,246],"replication,":[240],"code":[242],"developed":[243],"available":[248],"at":[249],"https://github.com/ShuGuoJ/GiGCN.git.":[250]},"counts_by_year":[{"year":2026,"cited_by_count":11},{"year":2025,"cited_by_count":61},{"year":2024,"cited_by_count":55},{"year":2023,"cited_by_count":25},{"year":2022,"cited_by_count":2}],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2025-10-10T00:00:00"}