{"id":"https://openalex.org/W4313476641","doi":"https://doi.org/10.1109/tgrs.2022.3233591","title":"Graph Meta Transfer Network for Heterogeneous Few-Shot Hyperspectral Image Classification","display_name":"Graph Meta Transfer Network for Heterogeneous Few-Shot Hyperspectral Image Classification","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4313476641","doi":"https://doi.org/10.1109/tgrs.2022.3233591"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2022.3233591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3233591","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":["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/A5100427190","display_name":"Haoyu Wang","orcid":"https://orcid.org/0000-0002-8905-822X"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Wang","raw_affiliation_strings":["Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","Xuzhou Key Laboratory of Artificial Intelligence and Big Data, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-8905-822X","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"Xuzhou Key Laboratory of Artificial Intelligence and Big Data, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108064895","display_name":"Xuesong Wang","orcid":"https://orcid.org/0000-0002-5327-1088"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuesong Wang","raw_affiliation_strings":["Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","Xuzhou Key Laboratory of Artificial Intelligence and Big Data, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5327-1088","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"Xuzhou Key Laboratory of Artificial Intelligence and Big Data, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091364297","display_name":"Yuhu Cheng","orcid":"https://orcid.org/0000-0003-2022-9999"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhu Cheng","raw_affiliation_strings":["Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","Xuzhou Key Laboratory of Artificial Intelligence and Big Data, China University of Mining and Technology, Xuzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-2022-9999","affiliations":[{"raw_affiliation_string":"Engineering Research Center of Intelligent Control for Underground Space, Ministry of Education, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]},{"raw_affiliation_string":"Xuzhou Key Laboratory of Artificial Intelligence and Big Data, China University of Mining and Technology, Xuzhou, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I25757504"],"apc_list":null,"apc_paid":null,"fwci":3.7516,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.93916252,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"12"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.961899995803833,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T13890","display_name":"Remote Sensing and Land Use","score":0.958899974822998,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8012651205062866},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7004870176315308},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6153770685195923},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5769591331481934},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.5691196322441101},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5107932090759277},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5001137256622314},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.439081609249115},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41369596123695374},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36973482370376587},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.13522973656654358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8012651205062866},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7004870176315308},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6153770685195923},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5769591331481934},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.5691196322441101},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5107932090759277},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5001137256622314},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.439081609249115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41369596123695374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36973482370376587},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.13522973656654358},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2022.3233591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2022.3233591","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"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.699999988079071,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G4756161396","display_name":null,"funder_award_id":"62176259","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6792490895","display_name":null,"funder_award_id":"61976215","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8143754585","display_name":null,"funder_award_id":"BE2022095","funder_id":"https://openalex.org/F4320327777","funder_display_name":"Jiangsu Provincial Key Research and Development Program"},{"id":"https://openalex.org/G8542357367","display_name":null,"funder_award_id":"BK20221116","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327777","display_name":"Jiangsu Provincial Key Research and Development Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2016860790","https://openalex.org/W2029316659","https://openalex.org/W2052684427","https://openalex.org/W2136251662","https://openalex.org/W2412588858","https://openalex.org/W2724081917","https://openalex.org/W2764276316","https://openalex.org/W2791006446","https://openalex.org/W2898204262","https://openalex.org/W2909487414","https://openalex.org/W2941141441","https://openalex.org/W2946948585","https://openalex.org/W2969899502","https://openalex.org/W2981501742","https://openalex.org/W2986799142","https://openalex.org/W2998247074","https://openalex.org/W3035667144","https://openalex.org/W3037458146","https://openalex.org/W3047443805","https://openalex.org/W3103695279","https://openalex.org/W3107769984","https://openalex.org/W3118357058","https://openalex.org/W3120660573","https://openalex.org/W3132867842","https://openalex.org/W3158900180","https://openalex.org/W3167649504","https://openalex.org/W3168464182","https://openalex.org/W3188824417","https://openalex.org/W3211917585","https://openalex.org/W3214955749","https://openalex.org/W3215576231","https://openalex.org/W4200258398","https://openalex.org/W4205102943","https://openalex.org/W4205276321","https://openalex.org/W4225685398","https://openalex.org/W4226044101","https://openalex.org/W4312307335","https://openalex.org/W4312772581","https://openalex.org/W6738964360","https://openalex.org/W6750109254"],"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/W2404757046","https://openalex.org/W2044184146","https://openalex.org/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3034864990"],"abstract_inverted_index":{"Since":[0],"obtaining":[1],"labeled":[2,29,41],"hyperspectral":[3],"images":[4],"(HSIs)":[5],"is":[6,126,146,170,209,236],"difficult":[7,67],"and":[8,59,103,107,138,153],"time-consuming,":[9],"the":[10,34,51,73,77,100,123,136,150,155,174,180,183,203,216,225,231,248],"shortage":[11],"of":[12,176,182,220],"training":[13],"samples":[14,30,42,213],"has":[15],"always":[16],"been":[17],"a":[18,27,86,117],"challenge":[19],"for":[20,132],"HSI":[21],"classification.":[22],"In":[23,120,201],"practical":[24],"applications,":[25],"only":[26],"few":[28],"are":[31,43,57,110,114],"available":[32,44],"in":[33,45,198,228],"task":[35],"domain":[36,47,75,226,233],"(target":[37],"domain),":[38],"while":[39],"sufficient":[40],"another":[46],"(source":[48],"domain).":[49],"At":[50],"same":[52],"time,":[53],"these":[54],"two":[55],"domains":[56],"heterogeneous":[58,88,229],"contain":[60],"different":[61,160],"categories.":[62,161],"This":[63],"scenario":[64],"makes":[65],"it":[66],"to":[68,76,148,172,189,193,211,223,238],"effectively":[69],"transfer":[70,96],"knowledge":[71],"from":[72,128],"source":[74,137],"target":[78,139],"domain.":[79],"To":[80],"address":[81],"this":[82,121],"challenge,":[83],"we":[84],"propose":[85],"novel":[87],"few-shot":[89,130],"learning":[90],"(FSL)":[91],"method,":[92],"namely":[93],"graph":[94,101],"meta":[95],"network":[97,105],"(GMTN).":[98],"Specifically,":[99],"sample":[102],"aggregate":[104],"(GraphSAGE)":[106],"meta-learning,":[108],"which":[109,186],"both":[111,199],"inductive":[112],"learning,":[113],"integrated":[115],"into":[116],"unified":[118],"framework.":[119],"way,":[122],"aggregation":[124],"function":[125],"generalized":[127],"abundant":[129],"tasks":[131],"feature":[133,151],"extraction":[134],"on":[135,215],"domains.":[140,200],"The":[141,162],"spatial":[142,205,217],"importance":[143,175],"strategy":[144,235],"(SIS)":[145],"designed":[147],"guide":[149],"propagation":[152],"alleviate":[154,224],"information":[156,181,206],"interference":[157],"caused":[158],"by":[159],"neighborhood":[163,184],"receptive":[164],"field":[165],"spectral":[166,177],"attention":[167,192],"(RFSA)":[168],"mechanism":[169],"proposed":[171,210],"model":[173],"band":[178],"using":[179],"pixels,":[185],"enables":[187],"GMTN":[188,246],"pay":[190],"more":[191],"bands":[194],"with":[195],"discriminative":[196],"features":[197],"addition,":[202],"node":[204],"reset":[207],"method":[208],"augment":[212],"based":[214],"position":[218],"relationship":[219],"nodes.":[221],"Furthermore,":[222],"shift":[227],"scenarios,":[230],"conditional":[232],"adversarial":[234],"used":[237],"achieve":[239],"effective":[240],"meta-knowledge":[241],"transfer.":[242],"Experiments":[243],"show":[244],"that":[245],"outperforms":[247],"compared":[249],"state-of-the-art":[250],"methods.":[251]},"counts_by_year":[{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":8}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
