{"id":"W1995585537","doi":"10.1117/12.2057413","title":"Fixed tile rate codec for bandwidth saving in video processors","year":2014,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Qualcomm (Canada)","funders":"","keywords":"Pixel; Computer science; Bitstream; Codec; Lossless compression; Data compression; Block size; Quantization (signal processing); Algorithm; Block (permutation group theory); Huffman coding; Computer hardware; Computer vision; Mathematics; Decoding methods","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":[0.0001737168,0.0003535119,0.000273274,0.0008526605,0.0003893183,0.0006368934,0.0008525155,0.0004149531,0.005935696],"category_scores_gemma":[0.0008638432,0.000114776,0.0002002822,0.001068411,0.0003149942,0.0005394768,0.000383957,0.0006201217,0.001838876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000724194,"about_ca_system_score_gemma":0.0005468394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001964486,"about_ca_topic_score_gemma":0.002437554,"domain_scores_codex":[0.9996351,0.00002795257,0.00001559922,0.00005230761,0.0002313153,0.00003769179],"domain_scores_gemma":[0.9995133,0.00007179093,0.00005719961,0.00008842959,0.0002470937,0.00002220991],"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":[0.000729173,0.0001145885,0.001388949,0.0005379639,0.00005201127,0.0006662454,0.0001622728,0.01185558,0.4580966,0.03226292,0.02577199,0.4683616],"study_design_scores_gemma":[0.0001180557,0.0007513486,0.003098384,0.0002030203,0.00009998276,0.002003778,0.00008049454,0.129373,0.6720046,0.0045359,0.1876114,0.0001199858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1548664,0.008002417,0.7593953,0.0009369613,0.001302939,0.0005939279,0.001388589,0.01056962,0.0629438],"genre_scores_gemma":[0.6660546,0.002842911,0.2669385,0.0007870626,0.0002501844,0.0004489833,0.002145298,0.001311855,0.05922066],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005935696,"threshold_uncertainty_score":0.01985687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01168198728610051,"score_gpt":0.2469165221821321,"score_spread":0.2352345348960315,"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."}}