{"id":"W2160560076","doi":"10.1109/icip.2009.5414225","title":"Logo insertion transcoding for H.264/AVC compressed video","year":2009,"lang":"en","type":"article","venue":"","topic":"Video Coding and Compression Technologies","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Transcoding; Computer science; Scalable Video Coding; Bit rate; Coding (social sciences); Real-time computing; Scheme (mathematics); Block (permutation group theory); Video quality; Computer hardware; Computer vision; Motion compensation; Computer network; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001610518,0.0001372058,0.0001700916,0.0001351498,0.0001999267,0.0001661255,0.001017745,0.0000963871,0.000009652084],"category_scores_gemma":[0.00005103285,0.0001123475,0.00009849906,0.0002596288,0.0000239143,0.0004116943,0.00006225822,0.0001068962,0.00001729943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000203835,"about_ca_system_score_gemma":0.0000212845,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005730185,"about_ca_topic_score_gemma":0.000001530449,"domain_scores_codex":[0.9989293,0.00002265188,0.0002232198,0.0003678283,0.0001676183,0.0002894029],"domain_scores_gemma":[0.999192,0.0001044043,0.00005873176,0.0005257212,0.00006686418,0.00005227765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002926359,0.0001283904,0.0000591108,0.00001822517,0.00001145622,0.000003573361,0.0002252037,0.0003192242,0.1092923,0.2952863,0.01433575,0.5802912],"study_design_scores_gemma":[0.001487819,0.0006829738,0.00239075,0.0001175184,0.00001129802,0.00001478214,0.00006975183,0.2268656,0.5486549,0.1941444,0.02499162,0.0005685725],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008769171,0.000143097,0.9773334,0.008080643,0.000209578,0.0002454459,8.854726e-7,0.001770425,0.003447376],"genre_scores_gemma":[0.9303934,0.0000200917,0.06808811,0.001066007,0.00002986926,0.00003174328,0.000001383209,0.000004663489,0.0003647457],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9216242,"threshold_uncertainty_score":0.4581397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02968614433951357,"score_gpt":0.2691324644105653,"score_spread":0.2394463200710517,"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."}}