{"id":"W2130567887","doi":"10.1109/ccece.2009.5090242","title":"The hardware architecture of a novel motion estimator with adaptive crossed quarter polar search patterns for H.264 encoding","year":2009,"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 Calgary","funders":"","keywords":"Motion estimation; Estimator; Computer science; Quarter-pixel motion; Block (permutation group theory); Encoding (memory); Hardware architecture; Computer hardware; Motion (physics); Architecture; Algorithm; Parallel computing; Computer vision; Artificial intelligence; Mathematics; Software","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":[0.0001381663,0.0002307926,0.0002067337,0.0003110538,0.0001631134,0.0002392138,0.0007201995,0.0002913809,0.002352223],"category_scores_gemma":[0.0003366393,0.000184705,0.0001490123,0.0002221141,0.00009186047,0.0004113216,0.0001834238,0.0002602321,0.0006742551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002300834,"about_ca_system_score_gemma":0.0004642204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001087349,"about_ca_topic_score_gemma":0.002043951,"domain_scores_codex":[0.9998834,0.00001476232,0.000009159405,0.00002320716,0.00005538086,0.00001402981],"domain_scores_gemma":[0.9998953,0.00001997975,0.00001687429,0.0000147662,0.00004554964,0.000007496032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004747419,0.0001016987,0.001782515,0.0002485451,0.00005852189,0.0003169448,0.00007470117,0.01063554,0.5871001,0.005242025,0.004009819,0.3899549],"study_design_scores_gemma":[0.0002624077,0.001975527,0.009580552,0.00006094687,0.0001639302,0.004265178,0.00005362716,0.3904557,0.5476007,0.00162005,0.04386431,0.00009706282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06444988,0.0005395566,0.9286348,0.0001748205,0.0001141826,0.0001521392,0.0001363733,0.002589951,0.003208282],"genre_scores_gemma":[0.4954057,0.0003569633,0.496971,0.0001890576,0.00006856269,0.0001552957,0.0003236599,0.00005714299,0.006472643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002352223,"threshold_uncertainty_score":0.007869005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027707002508912,"score_gpt":0.2701144606445441,"score_spread":0.239837390619455,"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."}}