{"id":"W3017927394","doi":"10.1117/12.2558889","title":"A deep learning based methodology for video anomaly detection in crowded scenes","year":2020,"lang":"en","type":"article","venue":"","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Anomaly detection; Artificial intelligence; Deep learning; Unsupervised learning; Autoencoder; Pattern recognition (psychology); Block (permutation group theory); Process (computing); Trajectory; Encoder; Supervised learning; Machine learning; Computer vision; Artificial neural network; Mathematics","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":[0.0005453986,0.0007081456,0.000584556,0.001256093,0.0003025027,0.000566449,0.001190292,0.0008255057,0.001103779],"category_scores_gemma":[0.00100638,0.0003453689,0.000663286,0.0008191328,0.0004979643,0.001004704,0.0009741083,0.00119825,0.0004024589],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008762601,"about_ca_system_score_gemma":0.0008659179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004735949,"about_ca_topic_score_gemma":0.004609975,"domain_scores_codex":[0.9995747,0.00005390552,0.00002695331,0.0001395594,0.0001502769,0.00005466498],"domain_scores_gemma":[0.9996963,0.00006087798,0.0000486976,0.00004040902,0.0001319813,0.000021874],"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":[0.0001113863,0.0001552298,0.002466841,0.0001585634,0.0001230025,0.0001841852,0.00009980318,0.1911732,0.04573119,0.0157725,0.003152099,0.740872],"study_design_scores_gemma":[0.000004048212,0.00005289993,0.0005833812,0.00001011764,0.00001109592,0.0001004565,0.00001016497,0.9829863,0.01104095,0.00337667,0.001813785,0.00001005294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004685267,0.0001277917,0.9939031,0.00006260665,0.00002488407,0.00004577863,0.00005898493,0.0006237069,0.0004678671],"genre_scores_gemma":[0.2669278,0.0004285082,0.7273219,0.0001823784,0.000069439,0.000200192,0.0005051101,0.00009247462,0.004272254],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004735949,"threshold_uncertainty_score":0.009416759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06895003938961532,"score_gpt":0.3090635816675826,"score_spread":0.2401135422779673,"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."}}