{"id":"https://openalex.org/W4410086606","doi":"https://doi.org/10.1109/lgrs.2025.3566955","title":"Hyperspectral Target Detection Based on Unsupervised Contrastive Learning and Spatial\u2013Spectral Knowledge Distillation","display_name":"Hyperspectral Target Detection Based on Unsupervised Contrastive Learning and Spatial\u2013Spectral Knowledge Distillation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4410086606","doi":"https://doi.org/10.1109/lgrs.2025.3566955"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2025.3566955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3566955","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/A5103508104","display_name":"Fan Mo","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":"Fan Mo","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0002-6079-1070","affiliations":[{"raw_affiliation_string":"School of Computer Science, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088024843","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":"https://openalex.org/A5011855820","display_name":"Xue\u2010Wei 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","Institute of Applied Ecology, CAS Key Laboratory of Forest Ecology and Silviculture, 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"]},{"raw_affiliation_string":"Institute of Applied Ecology, CAS Key Laboratory of Forest Ecology and Silviculture, Chinese Academy of Sciences, Shenyang, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210110024"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015198152","display_name":"Chuanyun Wang","orcid":"https://orcid.org/0000-0002-6737-3472"},"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":"Chuanyun Wang","raw_affiliation_strings":["College of Artificial Intelligence, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-6737-3472","affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Shenyang Aerospace University, Shenyang, China","institution_ids":["https://openalex.org/I125904092"]}]},{"author_position":"last","author":{"id":null,"display_name":"Bo Yuan","orcid":"https://orcid.org/0009-0002-3474-8300"},"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":"Bo Yuan","raw_affiliation_strings":["School of Computer Science, Shenyang Aerospace University, Shenyang, China"],"raw_orcid":"https://orcid.org/0009-0002-3474-8300","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":0.5419,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64195357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"22","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":0.9455999732017517,"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":0.9455999732017517,"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":0.9426000118255615,"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":0.9223758578300476},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6354895830154419},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5630053877830505},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.4740714132785797},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4731104373931885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3244500756263733},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12487846612930298}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9223758578300476},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6354895830154419},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5630053877830505},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4740714132785797},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4731104373931885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3244500756263733},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12487846612930298}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3566955","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3566955","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":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G1241236313","display_name":null,"funder_award_id":"2024-MS-137","funder_id":"https://openalex.org/F4320323086","funder_display_name":"Natural Science Foundation of Liaoning Province"},{"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"}],"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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W625476304","https://openalex.org/W1972578813","https://openalex.org/W2110211064","https://openalex.org/W2154236340","https://openalex.org/W2740976805","https://openalex.org/W2948763898","https://openalex.org/W3035524453","https://openalex.org/W3087782035","https://openalex.org/W3171007011","https://openalex.org/W3178914557","https://openalex.org/W4206307542","https://openalex.org/W4226038296","https://openalex.org/W4383428244","https://openalex.org/W4394773596","https://openalex.org/W4394938929","https://openalex.org/W4400877899","https://openalex.org/W4403827055","https://openalex.org/W6869337796"],"related_works":["https://openalex.org/W2385371209","https://openalex.org/W4250051149","https://openalex.org/W2083270190","https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296"],"abstract_inverted_index":{"Hyperspectral":[0],"target":[1,100],"detection":[2,101],"faces":[3],"challenges":[4],"due":[5],"to":[6,57,79],"limited":[7],"labeled":[8],"data":[9],"and":[10,44],"high":[11],"spectral":[12,41,59,82,89],"similarity":[13],"across":[14],"material":[15],"samples,":[16],"making":[17],"feature":[18,25,60,83],"extraction":[19,84],"difficult.":[20],"Existing":[21],"methods":[22,98],"for":[23],"spatial-spectral":[24,45,67],"learning":[26,43,55],"are":[27],"often":[28],"computationally":[29],"constrained.":[30],"To":[31],"address":[32],"these":[33],"issues,":[34],"we":[35],"propose":[36],"a":[37,75],"framework":[38],"combining":[39],"unsupervised":[40,53],"contrastive":[42,54],"knowledge":[46,68],"distillation":[47,69],"(UCLKD).":[48],"Our":[49],"approach":[50],"uses":[51],"an":[52],"module":[56],"enhance":[58],"representation":[61],"while":[62],"preventing":[63],"model":[64],"collapse.":[65],"A":[66],"strategy":[70],"then":[71],"leverages":[72],"features":[73],"from":[74],"hyperspectral":[76],"Foundation":[77],"Model":[78],"guide":[80],"the":[81],"network,":[85],"effectively":[86],"capturing":[87],"discriminative":[88],"features.":[90],"Extensive":[91],"experiments":[92],"demonstrate":[93],"that":[94],"UCLKD":[95],"outperforms":[96],"existing":[97],"in":[99],"performance.":[102],"The":[103],"code":[104],"is":[105],"available":[106],"at":[107],"https://github.com/Li-ZK/UCLKD.":[108]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}