{"id":"W2138501879","doi":"10.1109/iscas.1990.111999","title":"A very fast Kalman filter for image restoration","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Kalman filter; Image restoration; Diagonal; Computer vision; Algorithm; Computer science; Artificial intelligence; Invariant extended Kalman filter; Mathematics; Image processing; Extended Kalman filter; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002403557,0.00006545529,0.00007153309,0.0000562577,0.00009293932,0.0002006375,0.0002855331,0.0000283879,0.00009973297],"category_scores_gemma":[0.00005187494,0.00005544251,0.00004965016,0.00012958,0.00001569695,0.000678619,0.00005084245,0.00004066186,0.0001601502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001465324,"about_ca_system_score_gemma":0.00000641347,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006285889,"about_ca_topic_score_gemma":0.000001307877,"domain_scores_codex":[0.99939,0.00004947607,0.0001081881,0.0001904537,0.0001077491,0.0001541015],"domain_scores_gemma":[0.99949,0.00009106101,0.00002632449,0.0002896957,0.00006610004,0.00003686747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002149755,0.000142577,0.00002802491,0.00003552479,0.00001785263,0.00004662584,0.001839979,0.00003096305,0.1018358,0.05163241,0.4326875,0.4116813],"study_design_scores_gemma":[0.00163209,0.0003704069,0.0005344662,0.00002250604,0.00001175637,0.00004695355,0.00002802744,0.7685719,0.09332153,0.01665928,0.118308,0.0004930368],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006136265,0.00003171271,0.9742727,0.001095155,0.0002277985,0.0001011649,7.346936e-7,0.0001102212,0.02354691],"genre_scores_gemma":[0.04020911,0.000003559707,0.9351559,0.001350723,0.0001503508,0.00001856749,0.000001714852,0.000007533351,0.0231025],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7685409,"threshold_uncertainty_score":0.226088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0434231957248464,"score_gpt":0.2863807961285558,"score_spread":0.2429576004037094,"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."}}