{"id":"W2007121943","doi":"10.1364/ao.49.004284","title":"Intensity invariant nonlinear correlation filtering in spatially disjoint noise","year":2010,"lang":"en","type":"article","venue":"Applied Optics","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Disjoint sets; Linear filter; Invariant (physics); Optics; Nonlinear system; Correlation; Noise (video); Filter (signal processing); Matched filter; Intensity (physics); Physics; Nonlinear filter; Bruit; Mathematics; Computer science; Mathematical analysis; Artificial intelligence; Filter design; Acoustics; Image (mathematics); Computer vision; Geometry","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":[0.0006163209,0.0005928009,0.0003998888,0.0003508549,0.0002011869,0.0003851573,0.0004291381,0.000489919,0.0004424514],"category_scores_gemma":[0.003041445,0.000156274,0.0002557208,0.0004148022,0.0008847808,0.0006566979,0.0005134071,0.0003460861,0.0001346242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005086549,"about_ca_system_score_gemma":0.0003164644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001008389,"about_ca_topic_score_gemma":0.001156441,"domain_scores_codex":[0.9995366,0.00008216655,0.00001391388,0.00008006081,0.0002284528,0.00005877978],"domain_scores_gemma":[0.9982152,0.0009891754,0.0004152222,0.0001284356,0.0001864751,0.00006554625],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00120415,0.0002005249,0.004025156,0.0001599097,0.0001595785,0.0006465075,0.0001979743,0.2996597,0.6080352,0.01990014,0.0002562845,0.06555482],"study_design_scores_gemma":[0.00002076879,0.0003299324,0.003336789,0.000009748705,0.00004628652,0.0002678047,0.00002496599,0.8372093,0.1557504,0.002625866,0.0003391199,0.00003900044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7345228,0.0002440718,0.2630667,0.00005945368,0.00001741356,0.00001355226,0.00002741927,0.0001581841,0.001890375],"genre_scores_gemma":[0.9666365,0.0001389863,0.03247301,0.00002623885,0.000015561,0.00001654073,0.00003682202,0.00001367055,0.000642673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001008389,"threshold_uncertainty_score":0.003690541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007856589320398535,"score_gpt":0.2069690413576384,"score_spread":0.1991124520372398,"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."}}