{"id":"https://openalex.org/W4404142552","doi":"https://doi.org/10.3390/rs16224149","title":"Tensor-Based Few-Shot Learning for Cross-Domain Hyperspectral Image Classification","display_name":"Tensor-Based Few-Shot Learning for Cross-Domain Hyperspectral Image Classification","publication_year":2024,"publication_date":"2024-11-07","ids":{"openalex":"https://openalex.org/W4404142552","doi":"https://doi.org/10.3390/rs16224149"},"language":"en","primary_location":{"id":"doi:10.3390/rs16224149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16224149","pdf_url":"https://www.mdpi.com/2072-4292/16/22/4149/pdf?version=1730972506","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/16/22/4149/pdf?version=1730972506","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071093674","display_name":"Haojin Tang","orcid":"https://orcid.org/0009-0007-9365-1484"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojin Tang","raw_affiliation_strings":["School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030052464","display_name":"Xiaofei Yang","orcid":"https://orcid.org/0000-0002-2713-9681"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaofei Yang","raw_affiliation_strings":["School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052842216","display_name":"Dong Tang","orcid":"https://orcid.org/0000-0002-2240-8395"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Tang","raw_affiliation_strings":["School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070049638","display_name":"Yuting Dong","orcid":"https://orcid.org/0000-0002-8894-4318"},"institutions":[{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yiru Dong","raw_affiliation_strings":["School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Communication Engineering, Guangzhou University, Guangzhou 511370, China","institution_ids":["https://openalex.org/I37987034"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425747","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0003-3062-399X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108264876","display_name":"Weixin Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weixin Xie","raw_affiliation_strings":["Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China"],"affiliations":[{"raw_affiliation_string":"Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5030052464"],"corresponding_institution_ids":["https://openalex.org/I37987034"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":1.1036,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.74915587,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"16","issue":"22","first_page":"4149","last_page":"4149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T12676","display_name":"Machine Learning and ELM","score":0.9968000054359436,"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/T12303","display_name":"Tensor decomposition and applications","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6785553693771362},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.45235732197761536},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.41982728242874146},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.41810792684555054},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3900918662548065},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34103792905807495},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.3356704115867615},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11774250864982605},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.05605009198188782}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6785553693771362},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.45235732197761536},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.41982728242874146},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.41810792684555054},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3900918662548065},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34103792905807495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3356704115867615},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11774250864982605},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.05605009198188782}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs16224149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16224149","pdf_url":"https://www.mdpi.com/2072-4292/16/22/4149/pdf?version=1730972506","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9d25dff679534d3ba99c22853f90c438","is_oa":true,"landing_page_url":"https://doaj.org/article/9d25dff679534d3ba99c22853f90c438","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":"Remote Sensing, Vol 16, Iss 22, p 4149 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs16224149","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs16224149","pdf_url":"https://www.mdpi.com/2072-4292/16/22/4149/pdf?version=1730972506","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2744261620","display_name":null,"funder_award_id":"2024A04J00225","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3935651936","display_name":null,"funder_award_id":"62301174","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5694192508","display_name":null,"funder_award_id":"20200826154022001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G598868478","display_name":null,"funder_award_id":"2024A04J2081","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":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4404142552.pdf"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W2024165284","https://openalex.org/W2138973222","https://openalex.org/W2472819217","https://openalex.org/W2515890997","https://openalex.org/W2572303978","https://openalex.org/W2601450892","https://openalex.org/W2752782242","https://openalex.org/W2764276316","https://openalex.org/W2783684775","https://openalex.org/W2800955846","https://openalex.org/W2898204262","https://openalex.org/W2902137659","https://openalex.org/W2947471972","https://openalex.org/W2961267935","https://openalex.org/W2963341924","https://openalex.org/W2964105864","https://openalex.org/W2970845903","https://openalex.org/W2980347982","https://openalex.org/W2997322677","https://openalex.org/W3000935552","https://openalex.org/W3012405452","https://openalex.org/W3023155298","https://openalex.org/W3064134516","https://openalex.org/W3083068801","https://openalex.org/W3091905774","https://openalex.org/W3132867842","https://openalex.org/W3153239684","https://openalex.org/W3164816634","https://openalex.org/W3172523270","https://openalex.org/W3174396556","https://openalex.org/W3176341011","https://openalex.org/W3189063576","https://openalex.org/W3208507302","https://openalex.org/W4226267130","https://openalex.org/W4240485910","https://openalex.org/W4283760989","https://openalex.org/W4288054357","https://openalex.org/W4310987264","https://openalex.org/W4312575074","https://openalex.org/W4312882064","https://openalex.org/W4318483117","https://openalex.org/W4362585356","https://openalex.org/W4384829706","https://openalex.org/W4387092571","https://openalex.org/W4387595369","https://openalex.org/W4388469817","https://openalex.org/W4388666322","https://openalex.org/W4390691517","https://openalex.org/W4391661462","https://openalex.org/W4394595727","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6743661861","https://openalex.org/W6753311412","https://openalex.org/W6767471572","https://openalex.org/W6791058016","https://openalex.org/W6799059858","https://openalex.org/W6848037945","https://openalex.org/W6857290604","https://openalex.org/W6857813283","https://openalex.org/W6861631770"],"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/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"Few-shot":[0],"learning":[1,107],"(FSL)":[2],"is":[3,63,175,224],"an":[4,44],"effective":[5],"solution":[6],"for":[7,98,114,177],"cross-domain":[8,86,115],"hyperspectral":[9],"image":[10],"(HSI)":[11],"classification,":[12,117],"which":[13,46,118],"could":[14],"address":[15],"the":[16,21,29,33,57,73,100,122,127,149,153,165,179,200,209,215,221,232,238],"limited":[17],"labeled":[18],"samples":[19],"of":[20,129,148,203,217],"target":[22],"domain.":[23],"Current":[24],"FSL":[25,245],"methods":[26],"mostly":[27],"utilize":[28],"3D-CNN":[30],"to":[31,42,65,94,120,124,143,163,198,212],"transform":[32],"spatial":[34,49,70,74],"and":[35,50,75,84,102,159,187,207,231],"spectral":[36,51,61,76,131,201,218],"information":[37,52,62,77,156],"into":[38],"a":[39,104,137,145,169,192],"single":[40],"feature":[41,183,195,202],"model":[43,123,142,174,211],"HSI,":[45,151],"means":[47],"that":[48,237],"are":[53],"treated":[54],"equally":[55,78],"in":[56,81],"feature-modeling":[58],"process.":[59],"However,":[60],"considered":[64],"be":[66],"more":[67],"domain-invariant":[68,130,180],"than":[69],"information.":[71],"Treating":[72],"may":[79],"result":[80],"parameter":[82],"redundancy":[83],"undesirable":[85],"classification":[87],"performance.":[88],"In":[89],"this":[90],"paper,":[91],"we":[92,134,190],"attempt":[93],"use":[95],"tensor":[96,139,182,194],"mathematics":[97],"modeling":[99,216],"HSI":[101,116,229],"propose":[103,136],"novel":[105],"few-shot":[106,111],"method,":[108],"called":[109],"tensor-based":[110,170],"Learning":[112],"(TFSL)":[113],"aims":[119],"guide":[121,208],"focus":[125],"on":[126,214,226],"extraction":[128],"dependencies.":[132,219],"Specifically,":[133],"first":[135],"spatial\u2013spectral":[138,155,181],"decomposition":[140],"(SSTD)":[141],"provide":[144],"mathematical":[146],"explanation":[147],"input":[150],"representing":[152],"local":[154,161],"as":[157],"1D":[158],"2D":[160],"tensors":[162,206],"reduce":[164],"data":[166],"redundancy.":[167],"Additionally,":[168],"hybrid":[171,204],"two-stream":[172,205],"(THT)":[173],"proposed":[176,222,239],"extracting":[178],"by":[184],"using":[185],"1D-CNN":[186,193],"2D-CNN.":[188],"Furthermore,":[189],"adopt":[191],"enhancement":[196],"block":[197],"enhance":[199],"THT":[210],"concentrate":[213],"Finally,":[220],"TFSL":[223,240],"evaluated":[225],"four":[227],"public":[228],"datasets,":[230],"extensive":[233],"experimental":[234],"results":[235],"demonstrate":[236],"significantly":[241],"outperforms":[242],"other":[243],"advanced":[244],"methods.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
