{"id":"W2765744821","doi":"10.1007/978-3-662-56006-8_2","title":"KINECT Face Recognition Using Occluded Area Localization Method","year":2017,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Artificial intelligence; Computer vision; Facial recognition system; Face (sociological concept); Orientation (vector space); Three-dimensional face recognition; Occlusion; Local binary patterns; Pattern recognition (psychology); Identification (biology); Image (mathematics); Face detection; Histogram; 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":[0.001038178,0.0005302122,0.0005325166,0.0008404408,0.0006682264,0.001024492,0.00244046,0.000470963,0.00004881087],"category_scores_gemma":[0.000218224,0.0004927746,0.000152788,0.0002999753,0.0003272055,0.001399883,0.001011829,0.000640523,0.00009150799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000272695,"about_ca_system_score_gemma":0.0004097279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005814927,"about_ca_topic_score_gemma":0.00004726791,"domain_scores_codex":[0.9963003,0.00008012759,0.0005138869,0.001588461,0.0009394599,0.0005777603],"domain_scores_gemma":[0.9970377,0.0003209796,0.0005897023,0.001454472,0.0004211134,0.000176047],"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":[0.000007745748,0.00002289427,0.00001527034,0.00003981034,0.000009888447,0.00005469234,0.0004443746,0.05851134,0.0009642562,0.0002631668,0.00005173581,0.9396148],"study_design_scores_gemma":[0.0002600352,0.00007652948,0.00001693338,0.0009429101,0.00001470949,0.00009179008,2.322857e-7,0.8806906,0.00924137,0.1071714,0.0008748451,0.0006186405],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000066154,0.0001452352,0.994228,0.0003076124,0.001891239,0.0004307858,0.00001244171,0.0001910289,0.002727502],"genre_scores_gemma":[0.02407626,0.00007417719,0.9735982,0.001432055,0.00043794,0.00001074453,0.00004930362,0.00004816765,0.0002731654],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9389962,"threshold_uncertainty_score":0.9997524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06203110054676792,"score_gpt":0.3083443143584312,"score_spread":0.2463132138116633,"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."}}