{"id":"W4310509728","doi":"10.48550/arxiv.2211.15751","title":"Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniques","year":2022,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; McMaster University","keywords":"Computer science; Analytics; Data science; Cloud computing; Enhanced Data Rates for GSM Evolution; Variety (cybernetics); Big data; SPARK (programming language); Intersection (aeronautics); Edge device; Edge computing; Digital forensics; Law enforcement; Computer security; Artificial intelligence; Data mining; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005796893,0.0002479658,0.0002811147,0.0004283079,0.0004060289,0.0002183845,0.001336394,0.0001949687,0.00001612626],"category_scores_gemma":[0.00001697756,0.0002978047,0.0001024857,0.0009127677,0.00007529396,0.0001524376,0.001802956,0.0005834844,0.00001526616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002579944,"about_ca_system_score_gemma":0.0001100458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007620693,"about_ca_topic_score_gemma":0.00002736285,"domain_scores_codex":[0.9981369,0.0001886126,0.000232584,0.001123711,0.00009981098,0.0002183609],"domain_scores_gemma":[0.9978157,0.0001766037,0.0002944645,0.001445098,0.0001454642,0.0001226368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002627875,0.0002512138,0.004579428,0.0001726026,0.000126064,0.00004069756,0.00008819336,0.02655825,0.00007706639,0.9570581,0.00262978,0.008392289],"study_design_scores_gemma":[0.0004717238,0.0004260751,0.008142214,0.0002221026,0.0001733657,0.00002471172,0.0002735989,0.7084211,0.00150455,0.06992193,0.2081003,0.002318357],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005928757,0.0001485994,0.9896523,0.00005450371,0.00008919822,0.000929289,0.0000768376,0.0008934691,0.002227015],"genre_scores_gemma":[0.9945618,0.0007290242,0.002521353,0.00008710509,0.00006125924,0.00008304302,0.00004878489,0.00002089223,0.001886731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.988633,"threshold_uncertainty_score":0.9999474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08017676908259376,"score_gpt":0.2189948728180969,"score_spread":0.1388181037355031,"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."}}