{"id":"W4252791518","doi":"10.24124/2015/bpgub1134","title":"Local binary pattern network: a deep learning approach for face recognition","year":2015,"lang":"en","type":"dissertation","venue":"","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Artificial intelligence; Pattern recognition (psychology); Computer science; Deep learning; Convolutional neural network; Face (sociological concept); Artificial neural network; Facial recognition system; Kernel (algebra); Binary classification; Similarity (geometry); Machine learning; Image (mathematics); Support vector machine; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004250565,0.0003091896,0.000314043,0.0001395939,0.00022825,0.0002012205,0.0004939699,0.0004471076,0.00005285571],"category_scores_gemma":[0.0000388284,0.0002835368,0.0001546954,0.0002527757,0.00001439424,0.0004671857,0.00007896563,0.0004150853,0.000200318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005771049,"about_ca_system_score_gemma":0.00009266259,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003866438,"about_ca_topic_score_gemma":0.00004190355,"domain_scores_codex":[0.9980478,0.000112666,0.0003374148,0.0006893211,0.0003673981,0.0004453994],"domain_scores_gemma":[0.9988812,0.00007953705,0.0002482181,0.0002736806,0.0003705425,0.0001468793],"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":[0.00005321947,0.0000724357,0.000007988595,0.0001796742,0.00002829548,0.000003019819,0.0008317416,0.007078832,0.00005808055,0.00002490164,0.02031499,0.9713468],"study_design_scores_gemma":[0.0007163243,0.0003094644,0.00007687285,0.0002482978,0.00004588524,0.000008709681,0.002700269,0.985204,0.0006259938,0.003775776,0.005601706,0.00068664],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002566318,0.0003269317,0.9775126,0.00004332091,0.0008197988,0.0006325016,0.000006139046,0.0003525944,0.01773978],"genre_scores_gemma":[0.4538798,0.0004487222,0.4192333,0.001480084,0.001806166,0.002903606,0.06434535,0.0003046887,0.05559823],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9781252,"threshold_uncertainty_score":0.9999617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03573657183100495,"score_gpt":0.2757015407519119,"score_spread":0.239964968920907,"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."}}