{"id":"W2116949261","doi":"10.1016/s0030-4018(99)00649-5","title":"Optical implementation of the sliced orthogonal nonlinear generalized correlation for images degraded by nonoverlapping background noise","year":2000,"lang":"en","type":"article","venue":"Optics Communications","topic":"Advanced Optical Imaging Technologies","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Correlation; Clutter; Optical correlator; Optics; Noise (video); Nonlinear system; Optical correlation; Joint (building); Computer science; Algorithm; Physics; Mathematics; Image (mathematics); Artificial intelligence; Fourier transform; Mathematical analysis; Telecommunications; Geometry; Radar","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":[0.0003211706,0.0004585956,0.00025681,0.0002244724,0.0002308049,0.0004256936,0.0004012484,0.0002728675,0.001032974],"category_scores_gemma":[0.0005251709,0.000139602,0.0002387927,0.0003262516,0.000363591,0.0003949672,0.0004844003,0.0002640497,0.0001830673],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003498704,"about_ca_system_score_gemma":0.0006014583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009806934,"about_ca_topic_score_gemma":0.003327317,"domain_scores_codex":[0.9998021,0.00005545309,0.000009303189,0.00002233976,0.0000787188,0.00003216211],"domain_scores_gemma":[0.9996319,0.00008352179,0.00006207463,0.00009030868,0.00009443324,0.00003774901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007431883,0.0001685442,0.001905444,0.0001891569,0.0001056934,0.0007566823,0.0002220424,0.04422648,0.7423296,0.1106335,0.001815398,0.09690429],"study_design_scores_gemma":[0.00004675348,0.0003280737,0.001432498,0.00003245519,0.00004334378,0.0007373247,0.00004607529,0.7006907,0.2830583,0.00841546,0.005110245,0.0000586589],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3444118,0.0004367622,0.6420556,0.000273464,0.0001418525,0.00008987194,0.0001496847,0.0007808061,0.01166002],"genre_scores_gemma":[0.7791415,0.0001918885,0.219016,0.00009637329,0.00003360191,0.00003493533,0.00008276676,0.00003720123,0.00136576],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001032974,"threshold_uncertainty_score":0.003455639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02572449800900149,"score_gpt":0.3048246359514578,"score_spread":0.2791001379424563,"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."}}