{"id":"https://openalex.org/W7147550768","doi":"https://doi.org/10.1109/cnml68938.2026.11452264","title":"Cross-view UAV Geo-localization via Wavelet-based Local Feature Enhancement","display_name":"Cross-view UAV Geo-localization via Wavelet-based Local Feature Enhancement","publication_year":2026,"publication_date":"2026-01-30","ids":{"openalex":"https://openalex.org/W7147550768","doi":"https://doi.org/10.1109/cnml68938.2026.11452264"},"language":null,"primary_location":{"id":"doi:10.1109/cnml68938.2026.11452264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-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/A5100374132","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0002-6570-5947"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["Huaqiao University,College of Information Science and Engineering,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University,College of Information Science and Engineering,Xiamen,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132623514","display_name":"Rui Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zhao","raw_affiliation_strings":["Huaqiao University,College of Information Science and Engineering,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University,College of Information Science and Engineering,Xiamen,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081644475","display_name":"Zhiping Lin","orcid":"https://orcid.org/0000-0001-8752-0532"},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiping Lin","raw_affiliation_strings":["Huaqiao University,College of Information Science and Engineering,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University,College of Information Science and Engineering,Xiamen,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132582754","display_name":"Zhenguo Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenguo Gao","raw_affiliation_strings":["Huaqiao University,Department of Computer Science and Technology,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University,Department of Computer Science and Technology,Xiamen,China","institution_ids":["https://openalex.org/I119045251"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5132652313","display_name":"Qing an Peng","orcid":null},"institutions":[{"id":"https://openalex.org/I119045251","display_name":"Huaqiao University","ror":"https://ror.org/03frdh605","country_code":"CN","type":"education","lineage":["https://openalex.org/I119045251"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing an Peng","raw_affiliation_strings":["Huaqiao University,College of Information Science and Engineering,Xiamen,China"],"affiliations":[{"raw_affiliation_string":"Huaqiao University,College of Information Science and Engineering,Xiamen,China","institution_ids":["https://openalex.org/I119045251"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5100374132"],"corresponding_institution_ids":["https://openalex.org/I119045251"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.86948767,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"848","last_page":"852"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.4607999920845032,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.4607999920845032,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.29989999532699585,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.07320000231266022,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6011000275611877},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5091000199317932},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.47870001196861267},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.4781000018119812},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.45350000262260437},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.4426000118255615},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.43939998745918274},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4372999966144562},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.421999990940094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7077000141143799},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6651999950408936},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6202999949455261},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6011000275611877},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5091000199317932},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.4781000018119812},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.45350000262260437},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.4426000118255615},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.43939998745918274},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4372999966144562},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4124999940395355},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.39169999957084656},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3723999857902527},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.28040000796318054},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.27459999918937683},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2727999985218048},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.267300009727478},{"id":"https://openalex.org/C2985909886","wikidata":"https://www.wikidata.org/wiki/Q193147","display_name":"Spatial coherence","level":3,"score":0.25290000438690186},{"id":"https://openalex.org/C2986492983","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image matching","level":3,"score":0.25279998779296875},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cnml68938.2026.11452264","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cnml68938.2026.11452264","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 International Conference on Communication Networks and Machine Learning (CNML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.4569331407546997,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2883311563","https://openalex.org/W3081227581","https://openalex.org/W3092933908","https://openalex.org/W3159320309","https://openalex.org/W4285246495","https://openalex.org/W4392543774","https://openalex.org/W4396594805","https://openalex.org/W4402917079","https://openalex.org/W4413553642","https://openalex.org/W4413980880","https://openalex.org/W4415547374","https://openalex.org/W4417002775"],"related_works":[],"abstract_inverted_index":{"Cross-view":[0],"image":[1],"matching":[2],"serves":[3],"as":[4,103],"a":[5,55,60,92,132],"pivotal":[6],"technology":[7],"for":[8],"UAV":[9,21],"autonomous":[10],"localization":[11,129],"and":[12,22,105],"navigation.":[13],"Yet,":[14],"given":[15],"the":[16,31,37,65,81,85,115,128,138],"severe":[17],"viewpoint":[18],"disparities":[19],"between":[20],"satellite":[23],"imagery,":[24],"current":[25],"approaches":[26],"often":[27],"fail":[28],"to":[29,75,90],"balance":[30],"extraction":[32],"of":[33,39,84,140],"global":[34],"semantics":[35],"with":[36,131,147],"preservation":[38],"fine-grained":[40],"local":[41,93],"details.":[42],"To":[43],"overcome":[44],"this":[45],"limitation,":[46],"we":[47],"present":[48],"an":[49],"enhanced":[50],"feature":[51,94],"model":[52],"built":[53],"upon":[54],"lightweight":[56,133],"backbone.":[57,135],"We":[58],"design":[59],"fusion":[61],"architecture":[62],"that":[63],"leverages":[64],"Unit":[66],"Spatial":[67],"Attention":[68],"Module":[69],"(USAM)":[70],"from":[71],"Lin":[72],"et":[73],"al.":[74],"target":[76],"salient":[77],"regions,":[78],"followed":[79],"by":[80],"innovative":[82],"integration":[83],"Discrete":[86],"Wavelet":[87],"Transform":[88],"(DWT)":[89],"establish":[91],"enhancement":[95],"module.":[96],"This":[97,136],"module":[98],"explicitly":[99],"captures":[100],"high-frequency":[101],"components\u2014such":[102],"edges":[104],"textures\u2014thereby":[106],"effectively":[107],"mitigating":[108],"spatial":[109,148],"information":[110],"loss":[111],"during":[112],"downsampling.":[113],"On":[114],"University-1652":[116],"benchmark,":[117],"our":[118,141],"method":[119],"delivers":[120],"highly":[121],"competitive":[122],"performance,":[123],"achieving":[124],"81.63%":[125],"R@1":[126],"in":[127,143],"task":[130],"ConvNeXt-Tiny":[134],"validates":[137],"efficacy":[139],"strategy":[142],"synergizing":[144],"frequency-domain":[145],"details":[146],"semantics.":[149]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-04-02T00:00:00"}