{"id":"W3209334811","doi":"10.11606/d.3.2021.tde-25102021-151818","title":"Convolutional neural network for distortion Classification in face images.","year":2021,"lang":"en","type":"dissertation","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Facial recognition system; Face (sociological concept); Distortion (music); Image quality; Deblurring; Pattern recognition (psychology); Computer vision; Three-dimensional face recognition; Artificial neural network; Image processing; Face detection; Image (mathematics); Image restoration","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001770684,0.0001623832,0.0002335401,0.0001433834,0.00009941582,0.0001502629,0.0002800369,0.0001687066,0.00009732343],"category_scores_gemma":[0.00005214188,0.0001683672,0.000192507,0.0005257323,0.00001153999,0.0002837439,0.00001862624,0.0001593714,0.00002763776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001154986,"about_ca_system_score_gemma":0.0001446058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003833363,"about_ca_topic_score_gemma":0.0008472651,"domain_scores_codex":[0.9986508,0.00005873802,0.0003540378,0.0004843208,0.0002284102,0.0002236295],"domain_scores_gemma":[0.9992067,0.00007883976,0.0001841319,0.0002355204,0.0002412268,0.00005355259],"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":[0.0001578057,0.0008955997,0.003799983,0.0008183936,0.0003734819,0.00002941947,0.001683099,0.01809255,0.006150682,0.1573236,0.1491375,0.6615379],"study_design_scores_gemma":[0.0006651467,0.00003544807,0.0608293,0.0001423346,0.0000624503,0.000003478213,0.0008385371,0.9267866,0.001005273,0.003685958,0.005307684,0.0006378063],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007095947,0.000979241,0.9807842,0.001485522,0.001814,0.0005069476,0.00003561409,0.000170994,0.007127522],"genre_scores_gemma":[0.8163951,0.0003616295,0.05227925,0.0007311735,0.000592176,0.0006690829,0.02713266,0.00005168541,0.1017872],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9285049,"threshold_uncertainty_score":0.6865814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02788596824395701,"score_gpt":0.2818846298281703,"score_spread":0.2539986615842133,"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."}}