{"id":"https://openalex.org/W4389161200","doi":"https://doi.org/10.1109/tgrs.2023.3336688","title":"Transfer Learning With Nonlinear Spectral Synthesis for Hyperspectral Target Detection","display_name":"Transfer Learning With Nonlinear Spectral Synthesis for Hyperspectral Target Detection","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4389161200","doi":"https://doi.org/10.1109/tgrs.2023.3336688"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3336688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3336688","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5009705011","display_name":"Yanzi Shi","orcid":"https://orcid.org/0000-0002-7717-985X"},"institutions":[{"id":"https://openalex.org/I25355098","display_name":"Chang'an University","ror":"https://ror.org/05mxya461","country_code":"CN","type":"education","lineage":["https://openalex.org/I25355098"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanzi Shi","raw_affiliation_strings":["School of Automobile, Chang’an University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-7717-985X","affiliations":[{"raw_affiliation_string":"School of Automobile, Chang’an University, Xi’an, China","institution_ids":["https://openalex.org/I25355098"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103849429","display_name":"Hua Cui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hua Cui","raw_affiliation_strings":["School of Information Engineering, Chang’an University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Chang’an University, Xi’an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109599767","display_name":"Yaping Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaping Yin","raw_affiliation_strings":["PLA Naval Submarine Academy, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PLA Naval Submarine Academy, Qingdao, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008672520","display_name":"Huansheng Song","orcid":"https://orcid.org/0000-0002-8590-0061"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huansheng Song","raw_affiliation_strings":["School of Information Engineering, Chang’an University, Xi’an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Chang’an University, Xi’an, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101862572","display_name":"Yunsong Li","orcid":"https://orcid.org/0000-0002-5239-6428"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunsong Li","raw_affiliation_strings":["State Key Laboratory of Integrated Service Network, Xidian University, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0002-5239-6428","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Integrated Service Network, Xidian University, Xi’an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006623289","display_name":"Paolo Gamba","orcid":"https://orcid.org/0000-0002-9576-6337"},"institutions":[{"id":"https://openalex.org/I25217355","display_name":"University of Pavia","ror":"https://ror.org/00s6t1f81","country_code":"IT","type":"education","lineage":["https://openalex.org/I25217355"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Gamba","raw_affiliation_strings":["Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy"],"raw_orcid":"https://orcid.org/0000-0002-9576-6337","affiliations":[{"raw_affiliation_string":"Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy","institution_ids":["https://openalex.org/I25217355"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4443,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.90558593,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998999834060669,"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":0.9998999834060669,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9922999739646912,"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":0.9912999868392944,"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":0.8679595589637756},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.70733243227005},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6543006896972656},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6350288391113281},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6023780107498169},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5143555402755737},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5102329254150391},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4959615170955658},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4552544355392456},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45090925693511963},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.45056384801864624},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3296529948711395},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.21853402256965637}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8679595589637756},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.70733243227005},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6543006896972656},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6350288391113281},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6023780107498169},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5143555402755737},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5102329254150391},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4959615170955658},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4552544355392456},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45090925693511963},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.45056384801864624},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3296529948711395},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.21853402256965637},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3336688","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3336688","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3013816952","display_name":null,"funder_award_id":"12171234","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5574511099","display_name":null,"funder_award_id":"2023M740366","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W625476304","https://openalex.org/W1899348529","https://openalex.org/W1963659868","https://openalex.org/W1985562997","https://openalex.org/W1990953362","https://openalex.org/W2020953322","https://openalex.org/W2073748771","https://openalex.org/W2096972831","https://openalex.org/W2103192805","https://openalex.org/W2163547919","https://openalex.org/W2163886442","https://openalex.org/W2312906878","https://openalex.org/W2542124184","https://openalex.org/W2568395358","https://openalex.org/W2767892373","https://openalex.org/W2772028350","https://openalex.org/W2800922456","https://openalex.org/W2886682357","https://openalex.org/W2922095228","https://openalex.org/W2922177059","https://openalex.org/W2945493762","https://openalex.org/W2951039757","https://openalex.org/W2974391216","https://openalex.org/W2975159970","https://openalex.org/W2980358775","https://openalex.org/W2982545969","https://openalex.org/W3021150190","https://openalex.org/W3033502405","https://openalex.org/W3045657924","https://openalex.org/W3087782035","https://openalex.org/W3096751897","https://openalex.org/W3097141235","https://openalex.org/W3156696558","https://openalex.org/W3172610471","https://openalex.org/W3195212285","https://openalex.org/W3212625467","https://openalex.org/W4205124618","https://openalex.org/W4221010218","https://openalex.org/W4224261559","https://openalex.org/W4225582357","https://openalex.org/W4225688999","https://openalex.org/W4226038296","https://openalex.org/W4285124347","https://openalex.org/W4288054357","https://openalex.org/W4312513514","https://openalex.org/W4312845279","https://openalex.org/W4313181698","https://openalex.org/W4319336416","https://openalex.org/W4323065005","https://openalex.org/W4379528702","https://openalex.org/W4386075872"],"related_works":["https://openalex.org/W2159052453","https://openalex.org/W3013693939","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2072166414","https://openalex.org/W2752972570","https://openalex.org/W4297051394","https://openalex.org/W3209970181","https://openalex.org/W2070598848","https://openalex.org/W2734887215"],"abstract_inverted_index":{"Spectral":[0],"distortion":[1],"severely":[2],"limits":[3],"detection":[4,30,175,192],"performance":[5],"in":[6,66],"hyperspectral":[7,28,178],"imagery,":[8],"while":[9],"feature":[10,117],"learning":[11,36,84],"with":[12,98,122,133],"neural":[13],"networks":[14],"could":[15,61],"provide":[16],"sufficient":[17],"capacity":[18],"to":[19,49,70,87,104,199],"enhance":[20],"spectral":[21,39,200],"consistency.":[22],"This":[23],"paper":[24],"designs":[25],"an":[26,95],"end-to-end":[27],"target":[29,52],"(HTD)":[31],"network":[32],"based":[33],"on":[34,176],"transfer":[35,83],"and":[37,53,77,112,126,170,183,189],"nonlinear":[38,51],"synthesis":[40],"(TLNSS).":[41],"We":[42],"first":[43],"utilize":[44],"bilinear":[45],"mixture":[46],"model":[47],"(BMM)":[48],"synthesize":[50],"background":[54,111],"spectra":[55],"for":[56,164],"training":[57],"sample":[58],"augmentation,":[59],"which":[60],"better":[62],"characterize":[63],"ground":[64],"objects":[65],"complex":[67],"environments.":[68],"Due":[69],"the":[71,75,80,107,115,127,134,140,144,181,186,194],"mutual":[72],"constraints":[73],"between":[74],"quantity":[76],"diversity":[78],"of":[79,110,173,185,197],"synthesized":[81],"spectra,":[82],"is":[85,120,131],"introduced":[86],"further":[88,190],"address":[89],"data":[90],"insufficiency.":[91],"Specifically,":[92],"we":[93,157],"propose":[94],"asymmetric":[96],"autoencoder":[97],"a":[99],"particularly":[100],"designed":[101],"multi-level":[102],"loss":[103],"maximally":[105],"distinguish":[106],"reconstruction":[108,159],"residuals":[109,160],"target,":[113],"where":[114],"multi-scale":[116],"extraction":[118],"sub-network":[119,130],"trained":[121],"abundant":[123],"reference":[124],"data,":[125],"simple":[128],"restoration":[129],"updated":[132],"simulated":[135],"spectra.":[136],"To":[137],"effectively":[138],"reconstruct":[139],"input":[141],"as":[142],"expected,":[143],"features":[145],"extracted":[146],"from":[147],"different":[148],"blocks":[149],"are":[150],"complementarily":[151],"integrated":[152],"through":[153],"residual":[154],"attention.":[155],"Lastly,":[156],"accumulate":[158],"across":[161],"all":[162],"levels":[163],"final":[165],"detection.":[166],"The":[167],"experimental":[168],"results":[169],"ablation":[171],"analysis":[172],"single-data":[174],"three":[177],"images":[179],"verify":[180],"superiority":[182],"effectiveness":[184],"proposed":[187],"method,":[188],"cross-data":[191],"consolidates":[193],"satisfactory":[195],"tolerance":[196],"TLNSS":[198],"variation.":[201]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}