{"id":"W4280555209","doi":"10.18280/isi.270207","title":"Detection and Localization of Abnormal Events for Smart Surveillance","year":2022,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Anomaly detection; Anomaly (physics); Convolutional neural network; Computer science; Artificial intelligence; Artificial neural network; Pattern recognition (psychology); Data mining; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003735115,0.00006718489,0.00009065813,0.0001503024,0.000452836,0.0000430515,0.0001722003,0.00002941834,0.000005402323],"category_scores_gemma":[0.00003409286,0.00007486495,0.00003383841,0.0003905445,0.00002989907,0.00114574,0.0001171383,0.00004895551,0.000001299845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009474244,"about_ca_system_score_gemma":0.00002626988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004331842,"about_ca_topic_score_gemma":0.00000603289,"domain_scores_codex":[0.9993045,0.00003498439,0.000316943,0.00009313125,0.0001433106,0.0001070846],"domain_scores_gemma":[0.9993707,0.00003372889,0.0002563476,0.0001660742,0.0001467442,0.00002639837],"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":[0.0000861288,0.00007581888,0.01131915,0.0004374868,0.00003665383,1.798255e-7,0.004156743,0.008127808,0.001674596,0.07243422,0.0003630778,0.9012882],"study_design_scores_gemma":[0.0007432334,0.0006753842,0.02730838,0.00002207924,0.000009172793,0.0000840508,0.0005407872,0.8761629,0.01935952,0.03000307,0.04473378,0.0003576801],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04067559,0.00002444392,0.9583008,0.00002593622,0.0001095936,0.0003750567,0.00001976754,0.0001391093,0.000329681],"genre_scores_gemma":[0.9926579,0.00001062905,0.006840116,0.00006803105,0.00001059597,0.0003662877,0.00002389819,0.000003784605,0.0000187443],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9519823,"threshold_uncertainty_score":0.3482894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00967722663198644,"score_gpt":0.222751850712842,"score_spread":0.2130746240808556,"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."}}