{"id":"W2367010153","doi":"","title":"A New Fast Correlation Matching Algorithm Based on Grads Texture Characteristic","year":2004,"lang":"en","type":"article","venue":"Laser & Infrared","topic":"Advanced Measurement and Detection Methods","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"L'Alliance Boviteq","funders":"","keywords":"Similarity (geometry); Matching (statistics); Image (mathematics); Artificial intelligence; Computer science; Texture (cosmology); Tracking (education); Computer vision; Template matching; Algorithm; Correlation; Pattern recognition (psychology); Degree (music); Mathematics; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000950749,0.0001746481,0.0001459093,0.0001088959,0.00007393771,0.00003992588,0.00007145287,0.00009861936,0.000137021],"category_scores_gemma":[0.00003024837,0.0001773055,0.00006129996,0.0002152323,0.000007631221,0.0001761273,0.000006692563,0.0002554769,0.0001071425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001297656,"about_ca_system_score_gemma":0.00002857293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007566452,"about_ca_topic_score_gemma":0.000003855579,"domain_scores_codex":[0.9992253,0.00002118047,0.00018483,0.0001603321,0.0002103728,0.0001979928],"domain_scores_gemma":[0.9995891,0.00003645277,0.0000383964,0.0002017737,0.00002682367,0.0001074274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004050697,0.00002576469,0.00006141675,0.00003368216,0.00001990562,0.0000152117,0.0002821912,0.7752033,0.007912574,0.00008156089,0.0006462064,0.2156776],"study_design_scores_gemma":[0.009899024,0.0005374301,0.02538846,0.0007949299,0.0001520172,0.00003155265,0.0002240103,0.7588388,0.09730945,0.03619956,0.068469,0.00215574],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004239754,0.00003041064,0.9901878,0.00004209595,0.00091164,0.0001516281,0.00001113145,0.0005259613,0.003899565],"genre_scores_gemma":[0.5226591,0.00001298546,0.4729725,0.0007280531,0.0007985629,0.00004481685,0.0001254194,0.0001218146,0.002536709],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5184194,"threshold_uncertainty_score":0.7230308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009924296426865379,"score_gpt":0.2300164898927496,"score_spread":0.2200921934658842,"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."}}