{"id":"W2800965467","doi":"10.1117/12.2304896","title":"Deep learning for face recognition at a distance","year":2018,"lang":"en","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton","funders":"","keywords":"Artificial intelligence; Computer science; Face (sociological concept); Facial recognition system; Deep learning; Architecture; Computer vision; Pattern recognition (psychology); Convolutional neural network; Generative grammar; Geography","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":[0.0004273547,0.0005697143,0.0005020196,0.0003600123,0.0001869206,0.0004444651,0.0008049047,0.0007994244,0.003317063],"category_scores_gemma":[0.000973739,0.000210753,0.0004620714,0.0003858081,0.0004519478,0.0008706739,0.0009224794,0.001464871,0.001549879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006571998,"about_ca_system_score_gemma":0.0004070183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002437402,"about_ca_topic_score_gemma":0.00273267,"domain_scores_codex":[0.9997315,0.00004450884,0.000008321307,0.00007341339,0.0001069666,0.00003526678],"domain_scores_gemma":[0.9998178,0.00006593829,0.00002038165,0.00004281175,0.00004179941,0.00001124232],"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":[0.0001720481,0.0001146078,0.001068723,0.0001644283,0.00009365725,0.0001197917,0.00006828456,0.2381574,0.04503143,0.03434046,0.008898295,0.6717709],"study_design_scores_gemma":[0.000004558096,0.00004014112,0.0004997704,0.00001621031,0.00001218966,0.00008140194,0.000009592301,0.9691867,0.0111956,0.01489875,0.004044014,0.00001117143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01450676,0.001900845,0.978227,0.0003728629,0.00009389607,0.0000286107,0.0001357297,0.001187436,0.003546769],"genre_scores_gemma":[0.5870681,0.002714291,0.3948886,0.0005488345,0.0001795885,0.00009679724,0.0007483517,0.0001644401,0.01359103],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003317063,"threshold_uncertainty_score":0.01109666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02554340696568182,"score_gpt":0.2575226797424954,"score_spread":0.2319792727768136,"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."}}