{"id":"W1993065986","doi":"10.1109/tip.2005.860350","title":"Error resilient pre/post-filtering for DCT-based block coding systems","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Image Processing","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Discrete cosine transform; Computer science; Robustness (evolution); Coding (social sciences); Transform coding; Data compression; Algorithm; Coding tree unit; Algorithmic efficiency; Coding gain; Lapped transform; Iterative reconstruction; Computer vision; Artificial intelligence; Decoding methods; Mathematics; Image (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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008021853,0.0006015449,0.0003641581,0.0004183893,0.000363173,0.000430436,0.0004122054,0.0007160591,0.0008949409],"category_scores_gemma":[0.002884286,0.0001867619,0.0002709554,0.0004112326,0.0004277692,0.0005573815,0.0002670387,0.0006488913,0.0004325692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003242018,"about_ca_system_score_gemma":0.0003451099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001041614,"about_ca_topic_score_gemma":0.001362739,"domain_scores_codex":[0.9994202,0.0001272602,0.00004730263,0.00006764607,0.000300357,0.00003731762],"domain_scores_gemma":[0.9986872,0.0006986163,0.0001849773,0.0001932961,0.0002108602,0.00002508441],"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":[0.0005336431,0.0001486681,0.001339879,0.0002864132,0.00004978553,0.0003439581,0.0001538235,0.2489378,0.3219627,0.02774404,0.002241274,0.3962581],"study_design_scores_gemma":[0.00002614425,0.0003260412,0.0007645423,0.00003643121,0.00002962905,0.0005100065,0.00002252628,0.8535597,0.1340581,0.005728435,0.004907104,0.00003131302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02011979,0.0005131835,0.9780886,0.00008721311,0.00002903364,0.00003868305,0.00002049453,0.0002639391,0.0008390247],"genre_scores_gemma":[0.4447816,0.001457591,0.5498211,0.0001439948,0.0001073761,0.0001072802,0.0001619116,0.0000901325,0.003328976],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001041614,"threshold_uncertainty_score":0.00424242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02350781649770739,"score_gpt":0.3066500860939181,"score_spread":0.2831422695962107,"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."}}