{"id":"https://openalex.org/W4409985904","doi":"https://doi.org/10.1109/jstars.2025.3565894","title":"Hyperspectral Image Few-Shot Classification Based on Spatial\u2013Spectral Information Complementation and Multilatent Domain Generalization","display_name":"Hyperspectral Image Few-Shot Classification Based on Spatial\u2013Spectral Information Complementation and Multilatent Domain Generalization","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409985904","doi":"https://doi.org/10.1109/jstars.2025.3565894"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2025.3565894","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3565894","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.2025.3565894","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024158290","display_name":"Qiushan Yu","orcid":"https://orcid.org/0009-0000-5938-9514"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qianhao Yu","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100424366","display_name":"Yong Wang","orcid":"https://orcid.org/0000-0001-7670-3958"},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Wang","raw_affiliation_strings":["School of Automation, Central South University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5024158290"],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":1.1922,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80126819,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"18","issue":null,"first_page":"13212","last_page":"13224"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9386000037193298,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9386000037193298,"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":0.9294000267982483,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8584263920783997},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.653914213180542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.649601399898529},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6311132907867432},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5675195455551147},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5606921911239624},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43221575021743774},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4103182554244995},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3651670217514038},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.32159772515296936},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19113489985466003},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.10467761754989624}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8584263920783997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.653914213180542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.649601399898529},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6311132907867432},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5675195455551147},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5606921911239624},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43221575021743774},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4103182554244995},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3651670217514038},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32159772515296936},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19113489985466003},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.10467761754989624},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2025.3565894","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3565894","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:754932fe51b64daa88ce2087d7cc998a","is_oa":true,"landing_page_url":"https://doaj.org/article/754932fe51b64daa88ce2087d7cc998a","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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 13212-13224 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2025.3565894","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2025.3565894","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W248389711","https://openalex.org/W1930624869","https://openalex.org/W1994168328","https://openalex.org/W2018482939","https://openalex.org/W2053615857","https://openalex.org/W2090424610","https://openalex.org/W2138583748","https://openalex.org/W2141461755","https://openalex.org/W2141567889","https://openalex.org/W2150566919","https://openalex.org/W2162698522","https://openalex.org/W2500751094","https://openalex.org/W2733200288","https://openalex.org/W2752782242","https://openalex.org/W2754507318","https://openalex.org/W2793272303","https://openalex.org/W2800371750","https://openalex.org/W2909590067","https://openalex.org/W2947058136","https://openalex.org/W2947471972","https://openalex.org/W2962770389","https://openalex.org/W2963857746","https://openalex.org/W2964105864","https://openalex.org/W2985868110","https://openalex.org/W2998247074","https://openalex.org/W2998653622","https://openalex.org/W3006703771","https://openalex.org/W3011495011","https://openalex.org/W3012405452","https://openalex.org/W3025582806","https://openalex.org/W3036990306","https://openalex.org/W3044090999","https://openalex.org/W3049655825","https://openalex.org/W3064134516","https://openalex.org/W3122028341","https://openalex.org/W3126219352","https://openalex.org/W3202024712","https://openalex.org/W4210794570","https://openalex.org/W4239510810","https://openalex.org/W4285106080","https://openalex.org/W4285208279","https://openalex.org/W4287180559","https://openalex.org/W4296339430","https://openalex.org/W4303968625","https://openalex.org/W4313555298","https://openalex.org/W4327522253","https://openalex.org/W4385245566","https://openalex.org/W4390204423","https://openalex.org/W4391541676","https://openalex.org/W4400062972","https://openalex.org/W6678914141","https://openalex.org/W6755977528"],"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/W2990774877","https://openalex.org/W3093339210"],"abstract_inverted_index":{"Hyperspectral":[0],"image":[1],"(HSI)":[2],"few-shot":[3],"classification":[4,157,182,187,222],"aims":[5],"to":[6,46,86,104,130,154,165,184,205],"classify":[7],"HSI":[8,16,246],"samples":[9,17,74],"of":[10,18,75,140,160],"novel":[11,50],"categories":[12,44],"with":[13,109,118,220,232],"limited":[14],"training":[15],"base":[19,43,76,240],"categories.":[20,51,241],"However,":[21],"current":[22],"methods":[23],"suffer":[24],"from":[25],"two":[26,93,138],"issues:":[27],"1)":[28],"ignoring":[29],"the":[30,106,156,161,175,186,210,216,221,236],"complementary":[31,107,163],"relationship":[32],"between":[33,136],"spatial":[34,119,132],"and":[35,38,63,120,123,133,208],"spectral":[36,121,134],"information;":[37],"2)":[39],"performance":[40,237],"degradation":[41,238],"on":[42,49,239,244],"due":[45],"excessive":[47],"focus":[48],"This":[52],"paper":[53],"proposes":[54],"a":[55,79,125,147,181,191],"<italic":[56,59,64],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[57,60,65],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">s</i>patial-spectral":[58],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i</i>nformation":[61],"complementation":[62,99],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">m</i>ultilatent":[66],"domain":[67,193,203,233],"generalization-based":[68],"framework":[69],"(called":[70],"SIM).":[71],"Specifically,":[72],"given":[73],"(novel)":[77],"categories,":[78],"spatial-spectral":[80,89,97,126,172,176,230],"feature":[81,149,168],"extraction":[82],"network":[83,195],"is":[84,152,197],"designed":[85],"extract":[87,105,229],"their":[88],"features,":[90,141],"which":[91,199],"includes":[92],"steps.":[94],"First,":[95],"multiple":[96],"information":[98,127,135,144],"modules":[100],"(SSICs)":[101],"are":[102,178],"stacked":[103],"features":[108,117,164,177,231],"different":[110],"scales.":[111],"Note":[112],"that":[113,249],"each":[114],"SSIC":[115],"extracts":[116],"information,":[122],"adopts":[124],"transmission":[128],"unit":[129],"cross-transmit":[131],"these":[137],"types":[139],"thus":[142,170],"achieving":[143],"complementation.":[145],"Second,":[146],"multiscale":[148,162],"fusion":[150],"module":[151],"utilized":[153],"calculate":[155],"influence":[158],"scores":[159],"perform":[166],"layer-by-layer":[167],"fusion,":[169],"obtaining":[171],"features.":[173],"Afterward,":[174],"fed":[179],"into":[180],"head":[183],"obtain":[185],"results.":[188],"During":[189],"training,":[190],"multilatent":[192],"generalization":[194],"(MLDGN)":[196],"designed,":[198],"iteratively":[200],"assigns":[201],"pseudo":[202],"labels":[204],"all":[206],"samples,":[207],"calculates":[209],"sample":[211,217],"discrimination":[212,218],"loss.":[213],"SIM":[214,227,250],"combines":[215],"loss":[219],"losses":[223],"for":[224],"training.":[225],"Thus,":[226],"can":[228],"invariance,":[234],"alleviating":[235],"Extensive":[242],"results":[243],"four":[245],"datasets":[247],"demonstrate":[248],"outperforms":[251],"state-of-the-art":[252],"methods.":[253]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}