{"id":"https://openalex.org/W4390659328","doi":"https://doi.org/10.1109/lgrs.2024.3350659","title":"S2TNet: Spectral\u2013Spatial Triplet Network for Few-Shot Hyperspectral Image Classification","display_name":"S2TNet: Spectral\u2013Spatial Triplet Network for Few-Shot Hyperspectral Image Classification","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4390659328","doi":"https://doi.org/10.1109/lgrs.2024.3350659"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2024.3350659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3350659","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/A5109672238","display_name":"Guijie Yue","orcid":null},"institutions":[{"id":"https://openalex.org/I4210152042","display_name":"Beijing Polytechnic","ror":"https://ror.org/03xgzn792","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210152042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guijie Yue","raw_affiliation_strings":["School of Architecture and Surveying Engineering, Beijing Polytechnic College, Beijing, China","Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Architecture and Surveying Engineering, Beijing Polytechnic College, Beijing, China","institution_ids":["https://openalex.org/I4210152042"]},{"raw_affiliation_string":"Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100450721","display_name":"Ling Zhang","orcid":"https://orcid.org/0000-0001-8206-3408"},"institutions":[{"id":"https://openalex.org/I4210153872","display_name":"Jiangsu Maritime Institute","ror":"https://ror.org/04pekda06","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210153872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ling Zhang","raw_affiliation_strings":["School of Naval Architecture &#x0026; Ocean Engineering, Jiangsu Maritime Institute, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Naval Architecture &#x0026; Ocean Engineering, Jiangsu Maritime Institute, Nanjing, China","institution_ids":["https://openalex.org/I4210153872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054585852","display_name":"Yiyang Zhou","orcid":"https://orcid.org/0000-0002-2888-830X"},"institutions":[{"id":"https://openalex.org/I4401727007","display_name":"Hikvision (China)","ror":"https://ror.org/02jzypx27","country_code":null,"type":"company","lineage":["https://openalex.org/I4401727007"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiyang Zhou","raw_affiliation_strings":["Artificial Intelligence Laboratory, Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2888-830X","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Laboratory, Hangzhou Hikvision Digital Technology Company Ltd., Hangzhou, China","institution_ids":["https://openalex.org/I4401727007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100394395","display_name":"Yuxiang Wang","orcid":"https://orcid.org/0000-0002-7020-6843"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxiang Wang","raw_affiliation_strings":["College of Geography and Remote Sensing, Hohai University, Nanjing, China","Jiangsu Province Engineering Research Center of Water Resources and Environment Assessment Using Remote Sensing, Hohai University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Geography and Remote Sensing, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]},{"raw_affiliation_string":"Jiangsu Province Engineering Research Center of Water Resources and Environment Assessment Using Remote Sensing, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018243278","display_name":"Zhaohui Xue","orcid":"https://orcid.org/0000-0001-6253-2967"},"institutions":[{"id":"https://openalex.org/I163340411","display_name":"Hohai University","ror":"https://ror.org/01wd4xt90","country_code":"CN","type":"education","lineage":["https://openalex.org/I163340411"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaohui Xue","raw_affiliation_strings":["College of Geography and Remote Sensing, Hohai University, Nanjing, China","Jiangsu Province Engineering Research Center of Water Resources and Environment Assessment Using Remote Sensing, Hohai University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0001-6253-2967","affiliations":[{"raw_affiliation_string":"College of Geography and Remote Sensing, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]},{"raw_affiliation_string":"Jiangsu Province Engineering Research Center of Water Resources and Environment Assessment Using Remote Sensing, Hohai University, Nanjing, China","institution_ids":["https://openalex.org/I163340411"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0293,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86514595,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"21","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":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":0.9861000180244446,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9847999811172485,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8472075462341309},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7970274090766907},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6981081962585449},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6967580318450928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5636129975318909},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5293346643447876},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5085481405258179},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4850601255893707},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.4592222571372986},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4260326325893402},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37602996826171875},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2532675266265869},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13461408019065857}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8472075462341309},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7970274090766907},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6981081962585449},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6967580318450928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5636129975318909},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5293346643447876},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5085481405258179},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4850601255893707},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.4592222571372986},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4260326325893402},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37602996826171875},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2532675266265869},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13461408019065857},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2024.3350659","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3350659","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":[{"display_name":"Reduced inequalities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G179363741","display_name":"\u9ad8\u5149\u8c31\u9065\u611f\u5f71\u50cf\u534a\u76d1\u7763\u6df1\u5ea6\u5b66\u4e60\u4e0e\u5206\u7c7b\u7814\u7a76","funder_award_id":"41971279","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1827510721","display_name":null,"funder_award_id":"22KJD420001","funder_id":"https://openalex.org/F4320335440","funder_display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China"},{"id":"https://openalex.org/G2659737875","display_name":null,"funder_award_id":"42271324","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5116539810","display_name":null,"funder_award_id":"BK20221506","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G6956892774","display_name":null,"funder_award_id":"42201406","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7545187159","display_name":null,"funder_award_id":"BGY2022KY-06QT","funder_id":"https://openalex.org/F4320327285","funder_display_name":"Beijing Polytechnic College"}],"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/F4320327285","display_name":"Beijing Polytechnic College","ror":null},{"id":"https://openalex.org/F4320335440","display_name":"Natural Science Research of Jiangsu Higher Education Institutions of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2069231830","https://openalex.org/W2464755555","https://openalex.org/W2500751094","https://openalex.org/W2764276316","https://openalex.org/W2800371750","https://openalex.org/W2898204262","https://openalex.org/W3102714317","https://openalex.org/W3132867842","https://openalex.org/W3138725786","https://openalex.org/W3202805802","https://openalex.org/W3205614732","https://openalex.org/W4225630686","https://openalex.org/W4285106080","https://openalex.org/W4323338598"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3009056573","https://openalex.org/W2922073769","https://openalex.org/W4297676672","https://openalex.org/W4281702477","https://openalex.org/W4378510483","https://openalex.org/W4376166922","https://openalex.org/W2490526372","https://openalex.org/W2905024780"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"(DL)":[2],"has":[3],"shown":[4],"great":[5],"potential":[6],"for":[7,37,153],"hyperspectral":[8,132],"image":[9],"(HSI)":[10],"classification.":[11,40],"However,":[12],"DL":[13],"models":[14],"easily":[15],"get":[16],"trapped":[17],"into":[18],"overfitting":[19],"due":[20],"to":[21,55,73,103],"limited":[22],"training":[23,72],"samples.":[24],"To":[25],"overcome":[26],"this":[27],"issue,":[28],"a":[29,42,60],"novel":[30],"spectral\u2013spatial":[31,44,57],"triplet":[32,83,88],"network":[33,45],"(S2TNet)":[34],"is":[35,53,65,91,110],"proposed":[36,66,92],"few-shot":[38],"HSI":[39],"First,":[41],"lightweight":[43],"(SSN)":[46],"composed":[47],"of":[48,114,123,157,168],"1-D":[49],"and":[50,70,78,99,144,166],"2-D":[51],"convolution":[52],"introduced":[54],"extract":[56],"features.":[58],"Second,":[59],"hard":[61],"sample":[62,101],"selection":[63],"strategy":[64],"by":[67,93],"integrating":[68],"classification":[69],"contrast":[71],"deal":[74],"with":[75,142],"unbalanced":[76],"positive":[77,98],"negative":[79,100],"samples":[80,109,150],"in":[81,155,161],"traditional":[82],"networks.":[84],"Third,":[85],"an":[86],"enhanced":[87],"loss":[89],"function":[90],"considering":[94],"the":[95,105,120,124],"relationship":[96],"between":[97,107],"pairs":[102],"ensure":[104],"distance":[106],"homogeneous":[108],"smaller":[111],"than":[112],"that":[113,135],"heterogeneous":[115],"samples,":[116],"which":[117],"effectively":[118],"improves":[119],"discrimination":[121],"ability":[122],"model.":[125],"Experiments":[126],"conducted":[127],"on":[128],"two":[129],"widely":[130],"used":[131],"datasets":[133],"demonstrate":[134],"S2TNet":[136],"significantly":[137],"outperforms":[138],"other":[139],"related":[140],"methods,":[141],"0.81%\u201316.83%":[143],"1.40%\u201313.83%":[145],"improvements":[146],"(under":[147],"20":[148],"labeled":[149],"per":[151],"class":[152],"training)":[154],"terms":[156],"overall":[158],"accuracy":[159],"(OA)":[160],"Indian":[162],"Pine":[163],"(IP)":[164],"data":[165],"University":[167],"Pavia":[169],"(PU),":[170],"respectively.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}
