{"id":"https://openalex.org/W7155047636","doi":"https://doi.org/10.1109/ncc68160.2026.11479125","title":"UCRS: Uncertainty-Calibrated Region Sampling for Real-Time Small Object Detection in High-Resolution Images","display_name":"UCRS: Uncertainty-Calibrated Region Sampling for Real-Time Small Object Detection in High-Resolution Images","publication_year":2026,"publication_date":"2026-02-26","ids":{"openalex":"https://openalex.org/W7155047636","doi":"https://doi.org/10.1109/ncc68160.2026.11479125"},"language":null,"primary_location":{"id":"doi:10.1109/ncc68160.2026.11479125","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc68160.2026.11479125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 National Conference on Communications (NCC)","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/A5134153298","display_name":"Akash Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Akash Kumar","raw_affiliation_strings":["National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122155404","display_name":"Yerram Deekshith Kumar","orcid":null},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yerram Deekshith Kumar","raw_affiliation_strings":["National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116241624","display_name":"Kannuru Srinadh","orcid":null},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kannuru Srinadh","raw_affiliation_strings":["National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India","institution_ids":["https://openalex.org/I16292982"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087587421","display_name":"Upendra Kumar Sahoo","orcid":"https://orcid.org/0000-0003-0813-4751"},"institutions":[{"id":"https://openalex.org/I16292982","display_name":"National Institute of Technology Rourkela","ror":"https://ror.org/011gmn932","country_code":"IN","type":"education","lineage":["https://openalex.org/I16292982"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Upendra Kumar Sahoo","raw_affiliation_strings":["National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Institute of Technology Rourkela,Department of Electronics and Communication Engineering,Odisha,India","institution_ids":["https://openalex.org/I16292982"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59267899,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"418","last_page":"423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.45010000467300415,"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":0.45010000467300415,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.06830000132322311,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.06610000133514404,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4569000005722046},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.3831999897956848},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38199999928474426},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3817000091075897},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.375900000333786},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.34290000796318054}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6432999968528748},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6399999856948853},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5527999997138977},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4569000005722046},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3831999897956848},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38199999928474426},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.375900000333786},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.34290000796318054},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.30570000410079956},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3018999993801117},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28349998593330383},{"id":"https://openalex.org/C182521987","wikidata":"https://www.wikidata.org/wiki/Q2493877","display_name":"Viola\u2013Jones object detection framework","level":5,"score":0.2587999999523163},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ncc68160.2026.11479125","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ncc68160.2026.11479125","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 National Conference on Communications (NCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2014018052","https://openalex.org/W2565639579","https://openalex.org/W2963299996","https://openalex.org/W2963351448","https://openalex.org/W2963857746","https://openalex.org/W2982770724","https://openalex.org/W2989611864","https://openalex.org/W2989676862","https://openalex.org/W3009396058","https://openalex.org/W3014641072","https://openalex.org/W3096609285","https://openalex.org/W3160195350","https://openalex.org/W3208285567","https://openalex.org/W3208645658","https://openalex.org/W4226410580","https://openalex.org/W4307411363","https://openalex.org/W4312823573","https://openalex.org/W4406089820","https://openalex.org/W4409887058","https://openalex.org/W4412986175"],"related_works":[],"abstract_inverted_index":{"The":[0,53,64,98,110,210],"detection":[1,132],"of":[2,42,51,127,172],"objects":[3,43],"in":[4,44,47,61,124,170],"high-resolution":[5],"(HR)":[6],"images,":[7],"particularly":[8],"those":[9],"taken":[10],"by":[11,68,92,114,137,174],"surveillance":[12],"systems":[13],"or":[14],"unmanned":[15],"aerial":[16],"vehicles":[17],"(UAVs),":[18],"appears":[19],"to":[20,75,108,143,148],"be":[21],"a":[22,48,95,115,238],"significant":[23],"computational":[24,78],"bottleneck.":[25],"Additionally,":[26,160],"I":[27],"observe":[28],"that":[29,154,164],"when":[30],"traditional":[31],"methods":[32],"process":[33],"the":[34,39,69,128,151,161,195,229],"entire":[35],"input":[36],"domain":[37],"uniformly,":[38],"inherent":[40],"sparsity":[41],"backgrounds":[45],"results":[46,233],"great":[49],"deal":[50],"redundancy.":[52],"Uncertainty-Calibrated":[54],"Region":[55],"Sampling":[56],"(UCRS)":[57],"framework":[58,211],"is":[59,66,90,112,134],"presented":[60],"this":[62],"paper.":[63],"inefficiency":[65],"addressed":[67],"UCRS":[70,93,155,165,180],"framework,":[71],"which":[72],"uses":[73],"learning":[74],"dynamically":[76],"allocate":[77,101],"resources":[79,102],"and":[80,204,218,240,247],"measure":[81],"prediction":[82],"confidence":[83],"(<tex":[84,119],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[85,120,176,200,206,214,220],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mu,":[86],"\\sigma^{2}$</tex>).":[87],"Prediction":[88],"uncertainty":[89,235],"modeled":[91],"using":[94],"Gamma":[96],"distribution.":[97],"system":[99],"can":[100],"as":[103,237],"an":[104,252],"inference":[105],"problem":[106],"thanks":[107],"UCRS.":[109,125,138,145],"allocation":[111],"guided":[113],"Confidence-Weighted":[116],"Likelihood":[117],"Metric":[118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$E_{\\text":[121],"{conf":[122],"}}$</tex>)":[123],"Inspection":[126],"areas":[129],"with":[130,190],"anticipated":[131],"utility":[133],"given":[135],"priority":[136],"A":[139],"test":[140,152,162],"was":[141],"used":[142],"assess":[144],"When":[146],"compared":[147],"processing":[149],"techniques,":[150],"demonstrates":[153,163],"reduces":[156],"floating-point":[157],"operations":[158],"(FLOPs).":[159],"outperforms":[166],"deterministic":[167],"selection":[168],"heuristics":[169],"terms":[171],"precision":[173],"<tex":[175,199,205,213,219],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{5}-\\mathbf{8":[177],"\\%}$</tex>.":[178],"Notably,":[179],"maintains":[181,212],"real-time":[182],"performance":[183,224],"at":[184,225],"34.9":[185],"frames":[186],"per":[187],"second":[188],"(FPS)":[189],"only":[191],"52.5":[192],"GFLOPs":[193],"on":[194,228],"VisDrone":[196],"dataset,":[197],"achieving":[198],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$62.51":[201],"\\%":[202,208,216,222],"\\text{AP}_{50}$</tex>":[203],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$36.78":[207],"\\text{AP}$</tex>.":[209],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$55.01":[215],"\\text{AP}_{t}$</tex>":[217],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$70.25":[221],"\\text{AP}_{s}$</tex>":[223],"19.4":[226],"FPS":[227],"TinyPerson":[230],"dataset.":[231],"These":[232],"confirm":[234],"quantification":[236],"reliable":[239],"scalable":[241],"method":[242],"for":[243,257],"building":[244],"computationally":[245],"sustainable":[246],"flexible":[248],"perception":[249],"systems,":[250],"showing":[251],"excellent":[253],"efficiency-to-accuracy":[254],"trade-off":[255],"necessary":[256],"limited":[258],"edge":[259],"deployment.":[260]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-22T00:00:00"}
