{"id":"W2059928624","doi":"10.1109/icip.2013.6738327","title":"Confidence interval based motion estimation","year":2013,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Coding (social sciences); Computational complexity theory; Coding tree unit; Motion estimation; Bit rate; Rate distortion; Algorithm; Confidence interval; Context-adaptive binary arithmetic coding; Rate–distortion optimization; Algorithmic efficiency; Inference; Multiview Video Coding; Computer vision; Real-time computing; Artificial intelligence; Decoding methods; Mathematics; Data compression; Statistics; Video processing; Video tracking","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002661712,0.000867511,0.00115343,0.002188498,0.0002453009,0.00113504,0.001512233,0.0009591471,0.003128746],"category_scores_gemma":[0.02121822,0.0004113692,0.001015594,0.001436761,0.0003967297,0.001604085,0.001073683,0.001594713,0.0008330311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005101811,"about_ca_system_score_gemma":0.0007878446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002999917,"about_ca_topic_score_gemma":0.001982919,"domain_scores_codex":[0.9979725,0.0005859645,0.0001729863,0.0004287331,0.0007359405,0.000103878],"domain_scores_gemma":[0.9916058,0.005428138,0.0008357019,0.0006312627,0.001394676,0.0001044965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005353331,0.00008598057,0.004414721,0.0003167376,0.0002570853,0.0001333601,0.00009194095,0.25112,0.01429777,0.01684273,0.002782472,0.7091218],"study_design_scores_gemma":[0.00001904813,0.00006428239,0.001263541,0.00003058416,0.00003327512,0.0001434737,0.000009222982,0.9893388,0.004288537,0.003360317,0.001418115,0.0000307058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00386162,0.0005808156,0.99459,0.00004151836,0.00002336132,0.00001963395,0.00006842369,0.0002909517,0.0005236719],"genre_scores_gemma":[0.3680825,0.00127903,0.6263826,0.0001514104,0.0001564733,0.0001272256,0.001185151,0.0001789978,0.002456591],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003128746,"threshold_uncertainty_score":0.01407671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035051887635204,"score_gpt":0.2434869481962806,"score_spread":0.2231364293199286,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}