{"id":"https://openalex.org/W7164550918","doi":"https://doi.org/10.1109/access.2026.3703171","title":"A Feature-Refinement and Similarity-Learning Fusion Framework for Remote Sensing Image Retrieval","display_name":"A Feature-Refinement and Similarity-Learning Fusion Framework for Remote Sensing Image Retrieval","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7164550918","doi":"https://doi.org/10.1109/access.2026.3703171"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3703171","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3703171","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3703171","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120975621","display_name":"Tran Van Khanh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095101","display_name":"Hue University","ror":"https://ror.org/00qaa6j11","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210095101"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Tran van Khanh","raw_affiliation_strings":["University of Sciences, Hue University, Hue, Vietnam"],"raw_orcid":"https://orcid.org/0009-0008-0790-7760","affiliations":[{"raw_affiliation_string":"University of Sciences, Hue University, Hue, Vietnam","institution_ids":["https://openalex.org/I4210095101"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138511205","display_name":"Le Manh Thanh","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095101","display_name":"Hue University","ror":"https://ror.org/00qaa6j11","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210095101"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Le Manh Thanh","raw_affiliation_strings":["University of Sciences, Hue University, Hue, Vietnam"],"raw_orcid":"https://orcid.org/0000-0002-0949-222X","affiliations":[{"raw_affiliation_string":"University of Sciences, Hue University, Hue, Vietnam","institution_ids":["https://openalex.org/I4210095101"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043056693","display_name":"Nguy\u1ec5n Ng\u1ecdc Th\u1ee7y","orcid":"https://orcid.org/0000-0003-0541-0108"},"institutions":[{"id":"https://openalex.org/I4210095101","display_name":"Hue University","ror":"https://ror.org/00qaa6j11","country_code":"VN","type":"education","lineage":["https://openalex.org/I4210095101"]}],"countries":["VN"],"is_corresponding":false,"raw_author_name":"Nguyen Ngoc Thuy","raw_affiliation_strings":["University of Sciences, Hue University, Hue, Vietnam"],"raw_orcid":"https://orcid.org/0000-0003-0541-0108","affiliations":[{"raw_affiliation_string":"University of Sciences, Hue University, Hue, Vietnam","institution_ids":["https://openalex.org/I4210095101"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210095101"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.85266952,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"94413","last_page":"94433"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.36570000648498535,"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":0.36570000648498535,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.17309999465942383,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.07400000095367432,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.6054999828338623},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4503999948501587},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.44589999318122864},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4074999988079071},{"id":"https://openalex.org/keywords/remote-sensing-application","display_name":"Remote sensing application","score":0.3628999888896942},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33070001006126404},{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.3027999997138977}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7907000184059143},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7109000086784363},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.6054999828338623},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5396999716758728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48100000619888306},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4503999948501587},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.44589999318122864},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4074999988079071},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.3628999888896942},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33070001006126404},{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2921000123023987},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26499998569488525},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.26080000400543213},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.25060001015663147},{"id":"https://openalex.org/C87456703","wikidata":"https://www.wikidata.org/wiki/Q247760","display_name":"Radiometry","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3703171","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3703171","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7945d307f2b74279b41c3e0c89eff86b","is_oa":false,"landing_page_url":"https://doaj.org/article/7945d307f2b74279b41c3e0c89eff86b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 94413-94433 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3703171","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3703171","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Remote":[0],"sensing":[1,41],"image":[2,99],"retrieval":[3,36,104,119],"(RSIR)":[4],"has":[5],"been":[6],"significantly":[7,158],"enhanced":[8],"by":[9,121],"deep":[10,24,84],"convolutional":[11,147],"and":[12,57,80,143,148,173,190],"transformer-based":[13,149],"feature":[14,55,70,78,171,185],"representations.":[15,85],"However,":[16],"directly":[17],"applying":[18],"conventional":[19,106],"distance":[20],"measures":[21],"to":[22,28,34,60,76,94,117,193],"high-dimensional":[23],"features":[25],"often":[26],"fails":[27],"fully":[29],"capture":[30],"semantic":[31,62,96],"similarity,":[32],"leading":[33],"suboptimal":[35],"performance":[37],"in":[38,83],"complex":[39],"remote":[40],"scenes.":[42],"To":[43],"address":[44],"this":[45],"limitation,":[46],"we":[47],"propose":[48],"a":[49,67,87,110,188],"backbone-agnostic":[50],"refinement":[51],"framework":[52,130],"that":[53,154,178],"integrates":[54],"selection":[56,71],"similarity":[58,89,123,180],"learning":[59,90],"enhance":[61],"discrimination":[63],"for":[64,197],"RSIR.":[65,198],"Specifically,":[66],"genetic":[68],"algorithm\u2013based":[69],"strategy":[72],"is":[73,92,115,131],"first":[74],"employed":[75],"reduce":[77],"redundancy":[79],"suppress":[81],"noise":[82],"Subsequently,":[86],"supervised":[88],"module":[91],"introduced":[93],"learn":[95],"relationships":[97],"between":[98],"pairs,":[100],"enabling":[101],"more":[102],"discriminative":[103],"beyond":[105],"metric-based":[107],"matching.":[108],"Finally,":[109],"weighted":[111],"k-nearest":[112],"neighbor":[113],"scheme":[114],"adopted":[116],"stabilize":[118],"results":[120,152],"aggregating":[122],"information":[124],"from":[125],"local":[126],"neighborhoods.":[127],"The":[128],"proposed":[129,156],"extensively":[132],"evaluated":[133],"on":[134],"three":[135],"widely":[136],"used":[137],"RSIR":[138],"benchmarks,":[139],"including":[140],"WHU,":[141],"UCM,":[142],"SIRI,":[144],"using":[145],"multiple":[146],"back-bones.":[150],"Experimental":[151],"demonstrate":[153],"the":[155],"method":[157],"improves":[159],"mean":[160],"average":[161],"precision":[162],"over":[163],"state-of-the-art":[164],"approaches":[165],"while":[166],"maintaining":[167],"robustness":[168],"across":[169],"different":[170],"extractors":[172],"datasets.":[174],"These":[175],"findings":[176],"suggest":[177],"learning-based":[179],"refinement,":[181],"combined":[182],"with":[183],"effective":[184],"selection,":[186],"provides":[187],"powerful":[189],"flexible":[191],"alternative":[192],"end-to-end":[194],"model":[195],"retraining":[196]},"counts_by_year":[],"updated_date":"2026-06-29T08:53:18.405633","created_date":"2026-06-13T00:00:00"}
