{"id":"https://openalex.org/W7167478293","doi":"https://doi.org/10.3390/rs18132208","title":"Semantic Consistency and Uncertainty-Driven Small-Object Detection for Class Imbalance","display_name":"Semantic Consistency and Uncertainty-Driven Small-Object Detection for Class Imbalance","publication_year":2026,"publication_date":"2026-07-05","ids":{"openalex":"https://openalex.org/W7167478293","doi":"https://doi.org/10.3390/rs18132208"},"language":"en","primary_location":{"id":"doi:10.3390/rs18132208","doi":"https://doi.org/10.3390/rs18132208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18132208","pdf_url":"https://www.mdpi.com/2072-4292/18/13/2208/pdf?version=1783246751","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"parent_works":[],"lineage":["https://openalex.org/W7167478293"],"child_works_count":0,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/18/13/2208/pdf?version=1783246751","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135172747","display_name":"Nuo Chen","orcid":"https://orcid.org/0009-0000-2902-9817","observed_orcids":["https://orcid.org/0009-0000-2902-9817"]},"institutions":[{"id":"https://openalex.org/I2801618472","display_name":"PLA Rocket Force University of Engineering","ror":"https://ror.org/00gg5zj35","country_code":"CN","type":"education","lineage":["https://openalex.org/I2801618472"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nuo Chen","raw_affiliation_strings":["College of Operational Support, Rocket Force University of Engineering, Xi\u2019an 710025, China"],"raw_orcid":"https://orcid.org/0009-0000-2902-9817","affiliations":[{"raw_affiliation_string":"College of Operational Support, Rocket Force University of Engineering, Xi\u2019an 710025, China","institution_ids":["https://openalex.org/I2801618472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135121317","display_name":"Peng Zhao","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2801618472","display_name":"PLA Rocket Force University of Engineering","ror":"https://ror.org/00gg5zj35","country_code":"CN","type":"education","lineage":["https://openalex.org/I2801618472"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Peng Zhao","raw_affiliation_strings":["College of Operational Support, Rocket Force University of Engineering, Xi\u2019an 710025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Operational Support, Rocket Force University of Engineering, Xi\u2019an 710025, China","institution_ids":["https://openalex.org/I2801618472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5139512430","display_name":"Shouquan Hou","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I2801618472","display_name":"PLA Rocket Force University of Engineering","ror":"https://ror.org/00gg5zj35","country_code":"CN","type":"education","lineage":["https://openalex.org/I2801618472"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouquan Hou","raw_affiliation_strings":["College of Operational Support, Rocket Force University of Engineering, Xi\u2019an 710025, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Operational Support, Rocket Force University of Engineering, Xi\u2019an 710025, China","institution_ids":["https://openalex.org/I2801618472"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5135121317"],"corresponding_institution_ids":["https://openalex.org/I2801618472"],"apc_list":{"value":2700,"currency":"CHF","value_usd":3258},"apc_paid":{"value":2700,"currency":"CHF","value_usd":3258},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"18","issue":"13","first_page":"2208","last_page":"2208"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9955999851226807,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9955999851226807,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.0007999999797903001,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.0005000000237487257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/small-object-detection","display_name":"small object detection","score":0.9509999752044678},{"id":"https://openalex.org/keywords/class-imbalance","display_name":"class imbalance","score":0.8389999866485596},{"id":"https://openalex.org/keywords/aerial-images","display_name":"aerial images","score":0.6710000038146973},{"id":"https://openalex.org/keywords/uav-imagery","display_name":"UAV imagery","score":0.7110000252723694},{"id":"https://openalex.org/keywords/semantic-consistency","display_name":"semantic consistency","score":0.8920000195503235},{"id":"https://openalex.org/keywords/contrastive-learning","display_name":"contrastive learning","score":0.8410000205039978},{"id":"https://openalex.org/keywords/forecast-uncertainty","display_name":"forecast uncertainty","score":0.6790000200271606},{"id":"https://openalex.org/keywords/instance-selection","display_name":"instance selection","score":0.7910000085830688},{"id":"https://openalex.org/keywords/long-tailed-distributions","display_name":"long-tailed distributions","score":0.718999981880188},{"id":"https://openalex.org/keywords/dota","display_name":"DOTA","score":0.6320000290870667},{"id":"https://openalex.org/keywords/dior","display_name":"Dior","score":0.9950000047683716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8292999863624573},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8270000219345093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6777999997138977},{"id":"https://openalex.org/C150921843","wikidata":"https://www.wikidata.org/wiki/Q1170431","display_name":"Resampling","level":2,"score":0.5529999732971191},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5410000085830688},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5116999745368958},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.505299985408783},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4634000062942505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43650001287460327},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4300999939441681},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4253999888896942},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.3831000030040741},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.3206999897956848},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.304500013589859},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.29660001397132874},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.27730000019073486},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.257999986410141},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.25369998812675476},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.25}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs18132208","doi":"https://doi.org/10.3390/rs18132208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18132208","pdf_url":"https://www.mdpi.com/2072-4292/18/13/2208/pdf?version=1783246751","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d2efad84768b4781913bf8e3863a07b3","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/d2efad84768b4781913bf8e3863a07b3","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,"listed_in":[],"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":"Remote Sensing, Vol 18, Iss 13, p 2208 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs18132208","doi":"https://doi.org/10.3390/rs18132208","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18132208","pdf_url":"https://www.mdpi.com/2072-4292/18/13/2208/pdf?version=1783246751","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7167478293.pdf","grobid_xml":"https://content.openalex.org/works/W7167478293.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2798991696","https://openalex.org/W2799269579","https://openalex.org/W2948672349","https://openalex.org/W2963351448","https://openalex.org/W2963691377","https://openalex.org/W2964979676","https://openalex.org/W2983839017","https://openalex.org/W3021063507","https://openalex.org/W3034993937","https://openalex.org/W3113728373","https://openalex.org/W4387745459","https://openalex.org/W4388756758","https://openalex.org/W4389179984","https://openalex.org/W4393098647","https://openalex.org/W4394596587","https://openalex.org/W4396951816","https://openalex.org/W4401425866","https://openalex.org/W4404730777","https://openalex.org/W4404903809","https://openalex.org/W4405439138","https://openalex.org/W4405767056","https://openalex.org/W4406277426","https://openalex.org/W4406616680","https://openalex.org/W4407356371","https://openalex.org/W4407896957","https://openalex.org/W4409366556","https://openalex.org/W4409546112","https://openalex.org/W4409784663","https://openalex.org/W4410641367","https://openalex.org/W4411114697","https://openalex.org/W4411142602","https://openalex.org/W4411920919","https://openalex.org/W4412097793","https://openalex.org/W4412392661","https://openalex.org/W4412749935","https://openalex.org/W4413449500","https://openalex.org/W4414826019","https://openalex.org/W4415112538","https://openalex.org/W4415422420","https://openalex.org/W4415434062","https://openalex.org/W4416290769","https://openalex.org/W4417045386","https://openalex.org/W7101398669","https://openalex.org/W7106335850","https://openalex.org/W7113906405","https://openalex.org/W7119484525","https://openalex.org/W7125591240","https://openalex.org/W7127575143","https://openalex.org/W7131354381","https://openalex.org/W7133197332","https://openalex.org/W7155093639","https://openalex.org/W7161382627"],"related_works":["https://openalex.org/W4387929420","https://openalex.org/W4407407991","https://openalex.org/W4407356371","https://openalex.org/W4284972948","https://openalex.org/W7214942145","https://openalex.org/W7204146489","https://openalex.org/W4404787627","https://openalex.org/W7134973145","https://openalex.org/W7133788608","https://openalex.org/W4409452812"],"abstract_inverted_index":{"In":[0,85],"aerial":[1,146,149,202],"image":[2,150,203],"small-object":[3,204],"detection,":[4],"complex":[5],"imaging":[6],"perspectives,":[7],"arbitrary":[8],"object":[9],"orientations,":[10],"and":[11,24,98,123,172],"long-tailed":[12],"category":[13],"distributions":[14],"jointly":[15,119],"exacerbate":[16],"sample":[17,199],"imbalance,":[18],"which":[19],"significantly":[20,187],"degrades":[21],"detection":[22,180],"stability":[23],"leads":[25],"to":[26,63,94,130,152],"frequent":[27],"misclassification":[28],"of":[29,67,79,104,156,166,182,193],"minority":[30],"categories.":[31],"To":[32],"address":[33],"these":[34],"challenges,":[35],"this":[36],"paper":[37],"proposes":[38],"a":[39,53,87],"novel":[40],"training":[41],"framework":[42],"termed":[43],"SCUD.":[44],"Specifically,":[45],"in":[46,70,197,201],"the":[47,65,71,76,128,154,157,169,175,179,191,194],"label":[48],"noise":[49,96],"suppression":[50],"strategy":[51,90],"(LNSS),":[52],"contrastive":[54],"learning":[55,133],"mechanism":[56,114],"based":[57],"on":[58,82,141,168,174],"semantic":[59],"consistency":[60],"is":[61,92,116,186],"introduced":[62],"constrain":[64],"aggregation":[66],"similar":[68],"samples":[69,81],"feature":[72],"space,":[73],"thereby":[74],"reducing":[75],"adverse":[77],"impact":[78],"noisy":[80],"model":[83,129],"optimization.":[84],"addition,":[86],"scale-aware":[88],"resampling":[89],"(SARS)":[91],"designed":[93],"alleviate":[95],"amplification":[97],"overfitting":[99],"caused":[100],"by":[101,118],"excessive":[102],"repetition":[103],"small":[105],"objects":[106],"during":[107],"training.":[108],"Furthermore,":[109],"an":[110,164],"adaptive":[111],"instance":[112],"selection":[113],"(AISM)":[115],"developed":[117],"modeling":[120],"prediction":[121],"uncertainty":[122],"global":[124],"statistical":[125],"priors,":[126],"enabling":[127],"dynamically":[131],"emphasize":[132],"from":[134],"informative":[135],"samples.":[136],"Extensive":[137],"experiments":[138],"are":[139],"conducted":[140],"two":[142],"publicly":[143],"available":[144],"unmanned":[145],"vehicle":[147],"(UAV)":[148],"datasets":[151],"validate":[153],"effectiveness":[155,192],"proposed":[158,161,195],"approach.":[159],"The":[160],"method":[162,196],"achieves":[163],"mAP50":[165],"70.7%":[167],"DOTA-v1.0":[170],"dataset":[171],"88.1%":[173],"DIOR":[176],"dataset.":[177],"Notably,":[178],"accuracy":[181],"several":[183],"rare":[184],"categories":[185],"improved,":[188],"further":[189],"demonstrating":[190],"addressing":[198],"imbalance":[200],"detection.":[205]},"counts_by_year":[],"updated_date":"2026-11-10T11:39:43.021295","created_date":"2026-07-07T00:00:00"}