{"id":"W2144090983","doi":"10.1109/ccece.2009.5090178","title":"Region based searching for early terminated motion estimation algorithm of H.264/AVC video coding standard","year":2009,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Motion estimation; Quarter-pixel motion; Motion vector; Computer science; Encoder; Coding (social sciences); Context-adaptive variable-length coding; Algorithm; Motion compensation; Computer vision; Computational complexity theory; Scalable Video Coding; Block-matching algorithm; Computation; Artificial intelligence; Coding tree unit; Decoding methods; Mathematics; Video tracking; Video processing; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003657455,0.0001141925,0.0001749702,0.0002601857,0.0001596941,0.0001277455,0.000528949,0.00008329455,0.000001753721],"category_scores_gemma":[0.0001688778,0.00009809008,0.0000703679,0.0003386346,0.00003143558,0.0004860263,0.0000686187,0.0001068386,0.000001494054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004801035,"about_ca_system_score_gemma":0.00004037413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000159562,"about_ca_topic_score_gemma":4.028351e-7,"domain_scores_codex":[0.9989012,0.00004643722,0.0002613917,0.0002942529,0.0002789545,0.0002176888],"domain_scores_gemma":[0.9990844,0.0001431877,0.0001464442,0.0004095866,0.0001764717,0.00003997182],"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":[0.00001492938,0.00002684066,0.00004412526,0.00001649834,0.000002821681,0.00000240381,0.0001070393,0.0006565488,0.002359759,0.007900256,0.000375874,0.9884929],"study_design_scores_gemma":[0.0004379827,0.0004071731,0.0009116863,0.0001330689,0.000003637678,0.000003459422,0.00001910131,0.832262,0.1458773,0.01976966,0.00006581503,0.0001090722],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01625685,0.00001633579,0.9810163,0.001468394,0.00008470912,0.0002702345,0.000002377159,0.0007148355,0.0001699318],"genre_scores_gemma":[0.6584882,0.000002451316,0.3413492,0.00005744058,0.000007833897,0.00001077497,0.000002270108,0.000003580936,0.00007821685],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9883838,"threshold_uncertainty_score":0.3999997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02563530385917338,"score_gpt":0.2855897226291407,"score_spread":0.2599544187699673,"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."}}