{"id":"https://openalex.org/W3200705513","doi":"https://doi.org/10.1109/lgrs.2021.3108883","title":"Graph Neural Network via Edge Convolution for Hyperspectral Image Classification","display_name":"Graph Neural Network via Edge Convolution for Hyperspectral Image Classification","publication_year":2021,"publication_date":"2021-09-16","ids":{"openalex":"https://openalex.org/W3200705513","doi":"https://doi.org/10.1109/lgrs.2021.3108883","mag":"3200705513"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2021.3108883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3108883","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043672285","display_name":"Haojie Hu","orcid":"https://orcid.org/0000-0002-6645-8853"},"institutions":[{"id":"https://openalex.org/I4210126638","display_name":"Horological Research Institute of Light Industry","ror":"https://ror.org/031nqzs81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126638"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haojie Hu","raw_affiliation_strings":["Xi’an Research Institute of Hi-Tech, Xi’an, China","Xi'an Research Institute of Hi-Tech, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi’an Research Institute of Hi-Tech, Xi’an, China","institution_ids":[]},{"raw_affiliation_string":"Xi'an Research Institute of Hi-Tech, Xi'an, China","institution_ids":["https://openalex.org/I4210126638"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103550813","display_name":"Minli Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126638","display_name":"Horological Research Institute of Light Industry","ror":"https://ror.org/031nqzs81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126638"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minli Yao","raw_affiliation_strings":["Xi’an Research Institute of Hi-Tech, Xi’an, China","Xi'an Research Institute of Hi-Tech, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi’an Research Institute of Hi-Tech, Xi’an, China","institution_ids":[]},{"raw_affiliation_string":"Xi'an Research Institute of Hi-Tech, Xi'an, China","institution_ids":["https://openalex.org/I4210126638"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035860485","display_name":"Fang He","orcid":"https://orcid.org/0000-0003-0445-2568"},"institutions":[{"id":"https://openalex.org/I4210126638","display_name":"Horological Research Institute of Light Industry","ror":"https://ror.org/031nqzs81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126638"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fang He","raw_affiliation_strings":["Xi’an Research Institute of Hi-Tech, Xi’an, China","Xi'an Research Institute of Hi-Tech, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi’an Research Institute of Hi-Tech, Xi’an, China","institution_ids":[]},{"raw_affiliation_string":"Xi'an Research Institute of Hi-Tech, Xi'an, China","institution_ids":["https://openalex.org/I4210126638"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091458655","display_name":"Fenggan Zhang","orcid":"https://orcid.org/0000-0001-7997-9239"},"institutions":[{"id":"https://openalex.org/I4210126638","display_name":"Horological Research Institute of Light Industry","ror":"https://ror.org/031nqzs81","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210126638"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fenggan Zhang","raw_affiliation_strings":["Xi’an Research Institute of Hi-Tech, Xi’an, China","Xi'an Research Institute of Hi-Tech, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xi’an Research Institute of Hi-Tech, Xi’an, China","institution_ids":[]},{"raw_affiliation_string":"Xi'an Research Institute of Hi-Tech, Xi'an, China","institution_ids":["https://openalex.org/I4210126638"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043672285"],"corresponding_institution_ids":["https://openalex.org/I4210126638"],"apc_list":null,"apc_paid":null,"fwci":5.0512,"has_fulltext":false,"cited_by_count":55,"citation_normalized_percentile":{"value":0.95841008,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"19","issue":null,"first_page":"1","last_page":"5"},"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":0.9890999794006348,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9887999892234802,"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":0.8078600168228149},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7372808456420898},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7140849232673645},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7121648788452148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7118651270866394},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6569295525550842},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5419117212295532},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.532666802406311},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5041059255599976},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4734622836112976},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.46405425667762756},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43797725439071655},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4001126289367676},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.32352620363235474}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8078600168228149},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7372808456420898},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7140849232673645},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7121648788452148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7118651270866394},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6569295525550842},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5419117212295532},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.532666802406311},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5041059255599976},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4734622836112976},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46405425667762756},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43797725439071655},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4001126289367676},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.32352620363235474},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2021.3108883","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2021.3108883","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7900000214576721,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G4595938692","display_name":null,"funder_award_id":"6200010317","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1979158807","https://openalex.org/W2097092275","https://openalex.org/W2131864940","https://openalex.org/W2572303978","https://openalex.org/W2764276316","https://openalex.org/W2892621946","https://openalex.org/W2940678725","https://openalex.org/W2966751049","https://openalex.org/W2979750740","https://openalex.org/W2991494819","https://openalex.org/W3002244172","https://openalex.org/W3004968762","https://openalex.org/W3024007459","https://openalex.org/W3027629341","https://openalex.org/W3037458146","https://openalex.org/W3043181422","https://openalex.org/W3043183554","https://openalex.org/W3047443805","https://openalex.org/W3103695279","https://openalex.org/W3105997607","https://openalex.org/W3111727634","https://openalex.org/W3137391901","https://openalex.org/W3145049705","https://openalex.org/W3153131045","https://openalex.org/W3157130577","https://openalex.org/W4320339642","https://openalex.org/W6736685754"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2404757046","https://openalex.org/W2761785940","https://openalex.org/W2129933262","https://openalex.org/W2565656575"],"abstract_inverted_index":{"Graph":[0],"neural":[1,18],"network":[2,19],"(GNN)":[3],"has":[4],"recently":[5],"gained":[6],"increasing":[7],"attention":[8],"in":[9],"the":[10,25,51,65,68,74,95],"hyperspectral":[11],"image":[12],"(HSI)":[13],"classification.":[14],"Compared":[15],"with":[16,94],"convolutional":[17],"(CNN),":[20],"GNN":[21,43,61],"can":[22,88],"effectively":[23],"relieve":[24],"scarcity":[26],"of":[27,67],"labeled":[28],"data.":[29],"In":[30],"our":[31,86],"method,":[32],"we":[33,55],"first":[34],"perform":[35],"feature":[36],"learning":[37],"on":[38,77,80],"large-scale":[39],"irregular":[40],"regions":[41],"through":[42],"and":[44,71],"then":[45],"extract":[46],"local":[47],"spatial\u2013spectral":[48],"features":[49,76],"at":[50],"pixel":[52],"level.":[53],"Besides,":[54],"incorporate":[56],"edge":[57],"convolution":[58],"(EdgeConv)":[59],"into":[60],"to":[62],"adaptively":[63],"capture":[64],"interrelationship":[66],"representative":[69],"descriptors":[70],"fully":[72],"exploit":[73],"discriminative":[75],"graph.":[78],"Experiments":[79],"several":[81],"HSI":[82,97],"datasets":[83],"show":[84],"that":[85],"method":[87],"achieve":[89],"better":[90],"classification":[91,98],"performance":[92],"compared":[93],"state-of-the-art":[96],"methods.":[99]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":23},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":7}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}