{"id":"W7027029673","doi":"","title":"A Class of Augmented Convolutional Networks Architectures for Efficient Visual Anomaly Detection","year":2021,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Anomaly Detection Techniques and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Blackberry (Canada)","funders":"","keywords":"Anomaly detection; Autoencoder; Task (project management); Focus (optics); Generative grammar; Class (philosophy); Anomaly (physics); Convolutional neural network","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":[0.0004069341,0.0012236,0.000483542,0.0005540937,0.0002875904,0.000940709,0.001664309,0.000924986,0.003984571],"category_scores_gemma":[0.0009777932,0.0004399386,0.0007117826,0.0005301208,0.0004903075,0.001223729,0.001243834,0.001737591,0.001669364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008183222,"about_ca_system_score_gemma":0.0008314287,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005213227,"about_ca_topic_score_gemma":0.00831865,"domain_scores_codex":[0.9997327,0.00004114837,0.00001143541,0.00008432315,0.00007981508,0.00005058798],"domain_scores_gemma":[0.9997175,0.0000551608,0.00003422236,0.00008954915,0.00007588958,0.0000275878],"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":[0.0002596271,0.000174402,0.001431927,0.0002214926,0.0002080187,0.0002474711,0.00008093016,0.3530942,0.03068759,0.06512035,0.020494,0.52798],"study_design_scores_gemma":[0.000005131949,0.00003144776,0.0002861188,0.00001497645,0.00001718846,0.00005820162,0.000005512907,0.9792547,0.003846584,0.009326396,0.007143124,0.0000105917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02125321,0.001233076,0.9616785,0.0004370615,0.0002326681,0.00007615465,0.000432444,0.00385283,0.01080413],"genre_scores_gemma":[0.6030511,0.002476212,0.3557522,0.0006170908,0.0002762915,0.0002456096,0.002200272,0.000407653,0.03497361],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005213227,"threshold_uncertainty_score":0.01332974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006549298017572746,"score_gpt":0.2138569721686656,"score_spread":0.2073076741510929,"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."}}