{"id":"W4244753645","doi":"10.24124/2018/58868","title":"Face recognition using convolutional macropixel comparison approach","year":2018,"lang":"en","type":"dissertation","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Convolutional neural network; Artificial intelligence; Computer science; Deep learning; Facial recognition system; Face (sociological concept); Scope (computer science); Field (mathematics); Pattern recognition (psychology); Pixel; Machine learning; 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":[0.0003110135,0.0003853758,0.0005280227,0.0009385658,0.0002189317,0.0005227295,0.0007023916,0.0004165747,0.003116423],"category_scores_gemma":[0.0004402517,0.0001810215,0.0005374472,0.0004781054,0.0002301424,0.0007484394,0.0005366757,0.0003645084,0.0007117378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006100857,"about_ca_system_score_gemma":0.0004678778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003005008,"about_ca_topic_score_gemma":0.003794504,"domain_scores_codex":[0.9996498,0.00002518967,0.00001252954,0.0001137593,0.0001486126,0.00005022826],"domain_scores_gemma":[0.9998375,0.00002448319,0.00001709136,0.00002987692,0.00007872798,0.00001221893],"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":[0.0002247069,0.00009461626,0.002101597,0.0001125468,0.00009287184,0.0001093435,0.00005756883,0.03568077,0.1210515,0.008396907,0.003206452,0.8288712],"study_design_scores_gemma":[0.00001105789,0.0001384605,0.005067138,0.00001477527,0.00006809069,0.0004089469,0.00003292532,0.8777976,0.1059226,0.004051689,0.006460712,0.00002589706],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09630354,0.001180138,0.8902543,0.0001961433,0.0001438818,0.00008567061,0.0001663074,0.001529495,0.01014043],"genre_scores_gemma":[0.6051033,0.0008944645,0.3808412,0.0001838179,0.00009075916,0.00007548542,0.0004416447,0.0001249068,0.01224448],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003116423,"threshold_uncertainty_score":0.01042551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06928080691826752,"score_gpt":0.3155530666562653,"score_spread":0.2462722597379978,"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."}}