{"id":"W2071289785","doi":"10.2316/journal.206.2014.4.206-4086","title":"A SPARSE BASED RAIN REMOVAL ALGORITHM FOR IMAGE SEQUENCES","year":2014,"lang":"en","type":"article","venue":"International Journal of Robotics and Automation","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Image (mathematics); Computer science; Artificial intelligence; Algorithm; Pattern recognition (psychology); Computer vision","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004414309,0.000786352,0.0008725289,0.001213992,0.0004346666,0.0006883882,0.00111993,0.001077033,0.002438158],"category_scores_gemma":[0.001496544,0.0006554268,0.001005392,0.00112321,0.0004078491,0.0009449814,0.001145199,0.001254396,0.001708675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003290423,"about_ca_system_score_gemma":0.001053099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003298993,"about_ca_topic_score_gemma":0.005995465,"domain_scores_codex":[0.9995704,0.0000399598,0.00002229184,0.00006645277,0.0002576818,0.00004314525],"domain_scores_gemma":[0.9993679,0.0001778096,0.0000614708,0.0001039175,0.0002538721,0.00003505041],"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":[0.0002460532,0.0001149032,0.0005008692,0.000179888,0.00009850686,0.0001362024,0.0001053734,0.0559814,0.133962,0.004043078,0.004851791,0.7997799],"study_design_scores_gemma":[0.00003710289,0.0001237804,0.001231309,0.00002155284,0.0000678115,0.0004068364,0.00003045537,0.9292002,0.05711568,0.002769248,0.008960286,0.00003585123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003180037,0.0001177927,0.9957671,0.00004463805,0.00003086143,0.00002731684,0.00003238852,0.0004605323,0.0003393448],"genre_scores_gemma":[0.03050618,0.0003193665,0.9654052,0.00008991615,0.00007157196,0.00007067164,0.0003548665,0.0001724281,0.003009754],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003298993,"threshold_uncertainty_score":0.008156478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01540249960629796,"score_gpt":0.3003890235021301,"score_spread":0.2849865238958322,"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."}}