{"id":"https://openalex.org/W4411867111","doi":"https://doi.org/10.1109/jstars.2025.3584970","title":"Spatial Multifeature and Dual-Layer Multihop Graph Convolution Networks for Hyperspectral Image Classification","display_name":"Spatial Multifeature and Dual-Layer Multihop Graph Convolution Networks for Hyperspectral Image Classification","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411867111","doi":"https://doi.org/10.1109/jstars.2025.3584970"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3584970","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3584970","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/jstars.2025.3584970","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074666032","display_name":"Xiangyue Yu","orcid":null},"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/I4210088164","display_name":"Changchun Institute of Optics, Fine Mechanics and Physics","ror":"https://ror.org/012rct222","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyue Yu","raw_affiliation_strings":["Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China"],"raw_orcid":"https://orcid.org/0009-0002-1705-5465","affiliations":[{"raw_affiliation_string":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ning Li","orcid":"https://orcid.org/0009-0000-1885-1784"},"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/I4210088164","display_name":"Changchun Institute of Optics, Fine Mechanics and Physics","ror":"https://ror.org/012rct222","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Li","raw_affiliation_strings":["Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China"],"raw_orcid":"https://orcid.org/0009-0000-1885-1784","affiliations":[{"raw_affiliation_string":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072115830","display_name":"Di Wu","orcid":"https://orcid.org/0000-0002-4774-5515"},"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/I4210088164","display_name":"Changchun Institute of Optics, Fine Mechanics and Physics","ror":"https://ror.org/012rct222","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wu","raw_affiliation_strings":["Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101762239","display_name":"Zheng Li","orcid":"https://orcid.org/0000-0002-3078-1886"},"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/I4210088164","display_name":"Changchun Institute of Optics, Fine Mechanics and Physics","ror":"https://ror.org/012rct222","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Li","raw_affiliation_strings":["Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101767370","display_name":"Zhenyuan Wu","orcid":null},"institutions":[{"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":"Zhenyuan Wu","raw_affiliation_strings":["University of Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045303087","display_name":"Ximing Ma","orcid":null},"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/I4210088164","display_name":"Changchun Institute of Optics, Fine Mechanics and Physics","ror":"https://ror.org/012rct222","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ximing Ma","raw_affiliation_strings":["Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210088164"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":0.5419,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.66497131,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"18","issue":null,"first_page":"18391","last_page":"18410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9937000274658203,"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":0.9937000274658203,"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/T10057","display_name":"Face and Expression Recognition","score":0.9394000172615051,"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":0.9383999705314636,"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":0.7668381929397583},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7035830616950989},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5978944897651672},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5688123106956482},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5376390814781189},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4798664450645447},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46343547105789185},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4341356158256531},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4282413423061371},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.16235217452049255},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1298639178276062}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.7668381929397583},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7035830616950989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5978944897651672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5688123106956482},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5376390814781189},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4798664450645447},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46343547105789185},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4341356158256531},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4282413423061371},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.16235217452049255},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1298639178276062},{"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":2,"locations":[{"id":"doi:10.1109/jstars.2025.3584970","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3584970","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d3531edd9abc497e966ec0e4dfd15d0c","is_oa":true,"landing_page_url":"https://doaj.org/article/d3531edd9abc497e966ec0e4dfd15d0c","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 18391-18410 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3584970","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3584970","pdf_url":null,"source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W2136251662","https://openalex.org/W2261059368","https://openalex.org/W2519653196","https://openalex.org/W2614256707","https://openalex.org/W2764276316","https://openalex.org/W2948157022","https://openalex.org/W2992919850","https://openalex.org/W3004925702","https://openalex.org/W3014740345","https://openalex.org/W3020597450","https://openalex.org/W3023736619","https://openalex.org/W3024007459","https://openalex.org/W3034552520","https://openalex.org/W3047443805","https://openalex.org/W3049655825","https://openalex.org/W3107591966","https://openalex.org/W3114720220","https://openalex.org/W3114995754","https://openalex.org/W3125860323","https://openalex.org/W3132867842","https://openalex.org/W3157130577","https://openalex.org/W3171853541","https://openalex.org/W3177052299","https://openalex.org/W3184654054","https://openalex.org/W3213631637","https://openalex.org/W3214821343","https://openalex.org/W3215477434","https://openalex.org/W4210541032","https://openalex.org/W4210801462","https://openalex.org/W4214664134","https://openalex.org/W4226467560","https://openalex.org/W4281633835","https://openalex.org/W4293704264","https://openalex.org/W4318206819","https://openalex.org/W4318586076","https://openalex.org/W4322731396","https://openalex.org/W4327521838","https://openalex.org/W4327737145","https://openalex.org/W4362683584","https://openalex.org/W4368232741","https://openalex.org/W4378229647","https://openalex.org/W4386077592","https://openalex.org/W4386165662","https://openalex.org/W4388974348","https://openalex.org/W4391403325","https://openalex.org/W4391547538","https://openalex.org/W4392187922","https://openalex.org/W4392979581","https://openalex.org/W4394744688","https://openalex.org/W4394938888","https://openalex.org/W4400229457","https://openalex.org/W4401357744","https://openalex.org/W6726873649","https://openalex.org/W6771932116"],"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/W2070598848","https://openalex.org/W2019190440","https://openalex.org/W3034864990","https://openalex.org/W3088721469"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"classification":[3,212,219],"consti-tutes":[4],"a":[5,70,98,139,151,164,223],"crucial":[6],"research":[7,36],"direction":[8],"within":[9,107],"the":[10,45,59,108,114,130,136,160,181,185,189],"domain":[11],"of":[12,48,56,62,87,116,226],"remote":[13],"sensing.":[14],"Convolutional":[15],"neural":[16,22],"networks":[17,23],"(CNN)":[18],"and":[19,76,93,128,148,150,188],"graph":[20,79,101],"convo-lutional":[21],"(GCN)":[24],"have":[25],"exhibited":[26],"outstanding":[27],"clas-sification":[28],"performance":[29,220],"in":[30,43,133,208,218],"this":[31],"field,":[32],"emerging":[33],"as":[34,122],"current":[35],"focuses.":[37],"Nevertheless,":[38],"GCN":[39,109,186],"possesses":[40],"certain":[41],"limitations":[42],"cap-turing":[44],"neighborhood":[46],"features":[47,92,115,132,182],"images,":[49],"while":[50,175],"traditional":[51],"2D":[52],"CNNs":[53],"are":[54,192],"incapable":[55],"fully":[57],"extracting":[58,89],"spatial":[60,74,91,141],"information":[61,174],"HSI.":[63,134],"To":[64],"address":[65],"these":[66],"problems,":[67],"we":[68],"propose":[69],"novel":[71],"architecture":[72],"dubbed":[73],"multi-feature":[75],"dual-layer":[77,99],"multi-hop":[78,100],"convolutional":[80,102],"network":[81,84,103,123],"(SMTGCN).":[82],"This":[83],"is":[85,105,143,156,168],"capable":[86],"concurrently":[88],"pixel-level":[90],"superpix-el-level":[94],"spectral":[95],"features.":[96],"Specifically,":[97],"(DMGCN)":[104],"constructed":[106,144],"branch,":[110,138],"which":[111],"can":[112],"take":[113],"superpixel":[117,131],"at":[118],"differ-ent":[119],"segmentation":[120],"scales":[121],"nodes":[124],"to":[125,158,170,194],"effectively":[126],"capture":[127,162],"fuse":[129],"In":[135],"CNN":[137,190],"multi-scale":[140],"structure":[142,167],"for":[145],"feature":[146,161],"extraction":[147],"fusion,":[149],"hybrid":[152],"attention":[153],"mechanism":[154],"model":[155],"proposed":[157],"enhance":[159],"ability,":[163],"multi-layer":[165],"pooling":[166],"added":[169],"retain":[171],"more":[172],"detailed":[173],"sup-pressing":[176],"excessive":[177],"redundant":[178],"data.":[179],"Finally,":[180],"extracted":[183],"by":[184],"branch":[187,191],"fused":[193],"realize":[195],"HSI":[196,204],"classification.":[197],"Experimental":[198],"results":[199],"conducted":[200],"on":[201],"four":[202],"bench-mark":[203],"datasets":[205],"indicate":[206],"that,":[207],"comparison":[209],"with":[210],"existing":[211],"methods,":[213],"SMTGCN":[214],"achieves":[215],"remarkable":[216],"improve-ments":[217],"when":[221],"using":[222],"small":[224],"number":[225],"training":[227],"samples.":[228]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
