{"id":"W2008747262","doi":"10.1109/ccece.2008.4564892","title":"Towards an intelligent tele-surveillance system for public transport areas: Fuzzy logic based camera control","year":2008,"lang":"en","type":"article","venue":"Conference proceedings - Canadian Conference on Electrical and Computer Engineering","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Fuzzy logic; Fuzzy control system; Control (management); Intelligent control; Computer vision; Artificial intelligence; Real-time computing; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003678637,0.0003876747,0.0003063532,0.0003563837,0.0003280509,0.0009324578,0.0008352037,0.0007956435,0.00159818],"category_scores_gemma":[0.0004200181,0.0001582609,0.0002596675,0.0001871539,0.0003448601,0.0005187755,0.0002537552,0.0006436463,0.0003921113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004840282,"about_ca_system_score_gemma":0.0004674766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005691528,"about_ca_topic_score_gemma":0.004484077,"domain_scores_codex":[0.9997665,0.00002872454,0.00001243118,0.00006113192,0.00009744464,0.00003370659],"domain_scores_gemma":[0.999823,0.00002984736,0.00002482176,0.000009374314,0.00009480407,0.0000182773],"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":[0.0008311729,0.0005804993,0.002661423,0.0003408808,0.0001032974,0.0006553808,0.0006295062,0.07260914,0.4447522,0.01132507,0.00464767,0.4608638],"study_design_scores_gemma":[0.0001203919,0.0005366241,0.002136762,0.0000555611,0.0001069237,0.000295082,0.00009744898,0.9011528,0.08545087,0.001987069,0.008016347,0.00004413768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03624131,0.0003851906,0.9559307,0.0002079532,0.00008839402,0.0001699769,0.00003581629,0.001808531,0.005132185],"genre_scores_gemma":[0.7211328,0.0004598613,0.2707928,0.0003744558,0.0000717748,0.0001582196,0.00007831673,0.00004117897,0.006890619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005691528,"threshold_uncertainty_score":0.01131678,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03795392905076752,"score_gpt":0.2316211569878233,"score_spread":0.1936672279370558,"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."}}