{"id":"W54669815","doi":"10.1007/978-3-642-37410-4_9","title":"Block LBP Displacement Based Local Matching Approach for Human Face Recognition","year":2013,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Northern British Columbia","funders":"","keywords":"Local binary patterns; Voting; Majority rule; Computer science; Matching (statistics); Displacement (psychology); Block (permutation group theory); Artificial intelligence; Face (sociological concept); Rigidity (electromagnetism); Facial recognition system; Pattern recognition (psychology); Computer vision; Histogram; Politics; Mathematics; Statistics; Psychology; Political science; Image (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":[0.0002064973,0.0002540767,0.0005146433,0.0005854875,0.0002417414,0.0003215637,0.0007926611,0.0004186474,0.005229975],"category_scores_gemma":[0.0003087552,0.0001799259,0.0003831221,0.0005935195,0.0001576429,0.0003839288,0.0004250975,0.0003560939,0.002096861],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002736862,"about_ca_system_score_gemma":0.0004874764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00288573,"about_ca_topic_score_gemma":0.003629273,"domain_scores_codex":[0.9998041,0.00002201755,0.000007384782,0.00003446837,0.00010695,0.0000251599],"domain_scores_gemma":[0.9999044,0.00001478955,0.000005961304,0.00002331356,0.00004512263,0.000006352478],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002797893,0.000130274,0.0004263043,0.0001399219,0.00003685174,0.00006852798,0.00004160735,0.008637889,0.256072,0.002468802,0.004828798,0.7268691],"study_design_scores_gemma":[0.00004550375,0.0004605101,0.006635492,0.00002899749,0.0001037213,0.0008001279,0.00009997693,0.7925529,0.1806137,0.003372457,0.01524394,0.00004257655],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03607702,0.001107886,0.957274,0.0001020137,0.0001359393,0.0001215192,0.0002431622,0.001412059,0.003526408],"genre_scores_gemma":[0.3994345,0.001473953,0.5770382,0.0002176709,0.000104096,0.0002128684,0.001066376,0.0001791828,0.02027318],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005229975,"threshold_uncertainty_score":0.01749605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043726356879562,"score_gpt":0.2835370025942522,"score_spread":0.2530997390254566,"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."}}