{"id":"W1699515474","doi":"10.1109/icassp.1988.196767","title":"2-D Kalman filtering for the restoration of stochastically blurred images","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Kalman filter; Image restoration; Frame (networking); Computer science; Estimator; Noise (video); Computer vision; Artificial intelligence; Stochastic process; Algorithm; Mathematics; Image (mathematics); Image processing; Statistics","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":[0.0002387132,0.00006080309,0.00006866259,0.00003232476,0.00008767567,0.00005972086,0.0004077431,0.00001783823,0.000003749368],"category_scores_gemma":[0.0004139676,0.00004143772,0.00002571983,0.0001309604,0.00005237599,0.0004168151,0.00006084601,0.00003989954,0.000001089493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001196235,"about_ca_system_score_gemma":0.00003962137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001667763,"about_ca_topic_score_gemma":9.758917e-7,"domain_scores_codex":[0.999479,0.00001651161,0.0001395645,0.0001488258,0.0001020172,0.0001140674],"domain_scores_gemma":[0.9992406,0.000207308,0.00006606002,0.0003307231,0.000137412,0.00001789405],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001195036,0.0000575723,0.00002308423,0.0000559554,0.00001168191,9.363374e-7,0.000306312,0.0002569347,0.2959487,0.6286032,0.003139206,0.07158452],"study_design_scores_gemma":[0.0002716641,0.0001948899,0.000145404,0.00003954833,0.000008649627,0.00001092202,0.00003818416,0.2087926,0.627305,0.1582398,0.004751659,0.0002016424],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003664117,0.00009203161,0.9976049,0.0005445334,0.00006283205,0.0001812967,7.214878e-7,0.0001818848,0.001295151],"genre_scores_gemma":[0.1653679,0.000002905068,0.8343115,0.00008015341,0.000009051158,0.0000371296,2.390575e-7,0.000004629675,0.0001864693],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4703633,"threshold_uncertainty_score":0.1689781,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02427321357412882,"score_gpt":0.2980536159969815,"score_spread":0.2737804024228527,"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."}}