{"id":"https://openalex.org/W7082989946","doi":"https://doi.org/10.1109/lgrs.2025.3613444","title":"Multilevel Feature Score Learning for Few-Shot Open-Set Recognition of Hyperspectral Images","display_name":"Multilevel Feature Score Learning for Few-Shot Open-Set Recognition of Hyperspectral Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7082989946","doi":"https://doi.org/10.1109/lgrs.2025.3613444"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2025.3613444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3613444","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":null,"display_name":"Ziwei Zhang","orcid":"https://orcid.org/0009-0007-3384-7573"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziwei Zhang","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0007-3384-7573","affiliations":[{"raw_affiliation_string":"School of Computer Science, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhaokui Li","orcid":"https://orcid.org/0000-0002-5331-7664"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaokui Li","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-5331-7664","affiliations":[{"raw_affiliation_string":"School of Computer Science, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Wang","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xuewei Gong","orcid":"https://orcid.org/0000-0001-6715-5515"},"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/I4210110024","display_name":"Institute of Applied Ecology","ror":"https://ror.org/01thb7525","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewei Gong","raw_affiliation_strings":["CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-6715-5515","affiliations":[{"raw_affiliation_string":"CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110024"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jiaxu Guo","orcid":"https://orcid.org/0000-0001-8348-9283"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxu Guo","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0001-8348-9283","affiliations":[{"raw_affiliation_string":"School of Computer Science, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jing Tian","orcid":"https://orcid.org/0009-0007-9456-7030"},"institutions":[{"id":"https://openalex.org/I125904092","display_name":"Shenyang Aerospace University","ror":"https://ror.org/02423gm04","country_code":"CN","type":"education","lineage":["https://openalex.org/I125904092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Tian","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0007-9456-7030","affiliations":[{"raw_affiliation_string":"School of Computer Science, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5399,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91983742,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"22","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6514000296592712,"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"}},"topics":[{"id":"https://openalex.org/T12157","display_name":"Geochemistry and Geologic Mapping","score":0.6514000296592712,"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/T13067","display_name":"Geological Modeling and Analysis","score":0.025299999862909317,"subfield":{"id":"https://openalex.org/subfields/1906","display_name":"Geochemistry and Petrology"},"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/T14311","display_name":"Electrical and Electromagnetic Research","score":0.019999999552965164,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6891999840736389},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6614999771118164},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.546999990940094},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5123999714851379},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.4625000059604645},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.445499986410141},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4260999858379364},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.41769999265670776},{"id":"https://openalex.org/keywords/similarity-learning","display_name":"Similarity learning","score":0.4163999855518341}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7516999840736389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7146000266075134},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6891999840736389},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6614999771118164},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.546999990940094},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5123999714851379},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.4625000059604645},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4260999858379364},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C2779597229","wikidata":"https://www.wikidata.org/wiki/Q17146505","display_name":"Similarity learning","level":3,"score":0.4163999855518341},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.36579999327659607},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.33809998631477356},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.33719998598098755},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31360000371932983},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.305400013923645},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.30239999294281006},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25290000438690186},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3613444","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3613444","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":[],"awards":[{"id":"https://openalex.org/G5072407143","display_name":null,"funder_award_id":"KLFES-2035","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G5639436844","display_name":null,"funder_award_id":"62171295","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8899021661","display_name":null,"funder_award_id":"2025-BS-0320","funder_id":"https://openalex.org/F4320323086","funder_display_name":"Natural Science Foundation of Liaoning Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320323086","display_name":"Natural Science Foundation of Liaoning Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W3083068801","https://openalex.org/W4213037778","https://openalex.org/W4289641562","https://openalex.org/W4319301078","https://openalex.org/W4376851346","https://openalex.org/W4386075566","https://openalex.org/W4387042061","https://openalex.org/W4399169000","https://openalex.org/W4400229049","https://openalex.org/W4406171775","https://openalex.org/W4411043476","https://openalex.org/W4412030510"],"related_works":[],"abstract_inverted_index":{"Few-shot":[0],"open-set":[1],"recognition":[2],"(FSOSR)":[3],"for":[4,88],"hyperspectral":[5],"images":[6],"is":[7,96,150,190],"a":[8,19,84],"challenging":[9],"task":[10],"of":[11,23,118,131,139,157,172,186],"great":[12],"practical":[13],"value.":[14],"It":[15],"aims":[16],"to":[17,21,33,153,182],"classify":[18],"sample":[20,36],"one":[22],"the":[24,35,62,65,72,111,116,129,137,155,160,165,170,184],"known":[25,132,173],"classes":[26],"by":[27,168],"few":[28],"examples":[29],"while":[30,163],"being":[31],"able":[32],"reject":[34],"from":[37],"unknown":[38,140],"classes.":[39],"Prior":[40],"research":[41],"mainly":[42],"focus":[43],"on":[44,91,178],"high-level":[45],"semantic":[46,104],"features":[47,101,120],"and":[48,51,76,102,121,136,175],"ignore":[49],"mid-level":[50],"low-level":[52],"detailed":[53,107],"features.":[54],"Further,":[55],"recent":[56],"endeavors":[57],"in":[58],"generative":[59],"FSOSR":[60,86],"has":[61],"limitation":[63],"that":[64,128],"generated":[66],"samples":[67,133,141,174],"do":[68],"not":[69],"accurately":[70],"reflect":[71],"original":[73],"data":[74],"distribution":[75],"introduce":[77],"additional":[78],"noise.":[79],"To":[80],"solve":[81],"these":[82],"problems,":[83],"novel":[85],"method":[87],"HSI":[89,180],"based":[90],"multi-level":[92,100,119],"feature":[93],"score":[94,113,130,138],"learning":[95],"proposed,":[97],"which":[98],"considers":[99],"combines":[103],"information":[105],"with":[106],"information.":[108],"By":[109],"designing":[110],"multi-layer":[112],"fusion":[114],"module,":[115],"similarity":[117,146,162,167,171],"prototypes":[122],"are":[123,134,142],"converted":[124],"into":[125],"scores":[126],"so":[127],"lower":[135],"higher.":[143],"The":[144,188],"intra-inter":[145],"contrast":[147],"enhancement":[148],"module":[149],"also":[151],"introduced":[152],"enhance":[154],"discrimination":[156],"features,":[158],"increasing":[159],"intra-class":[161],"decreasing":[164],"inter-class":[166],"adjusting":[169],"prototypes.":[176],"Experiments":[177],"two":[179],"datasets":[181],"verify":[183],"effectiveness":[185],"MFSL.":[187],"code":[189],"available":[191],"at":[192],"https://github.com/Li-ZK/MFSL-2025.":[193]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}