{"id":"W2348555218","doi":"","title":"Robust face recognition based on low frequency DCT coefficients retransforming optimized by CLAHE","year":2014,"lang":"en","type":"article","venue":"Computer Engineering and Applications Journal","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Biological Sciences","funders":"","keywords":"Adaptive histogram equalization; Discrete cosine transform; Pattern recognition (psychology); Artificial intelligence; Computer science; Histogram; Facial recognition system; Classifier (UML); Histogram equalization; Kernel (algebra); Contrast (vision); Computer vision; Mathematics; 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":[0.0003167792,0.0003819375,0.0005482994,0.0006641891,0.0002521519,0.0004425828,0.0006434384,0.0003202903,0.001721016],"category_scores_gemma":[0.0008242249,0.0001832558,0.0003752359,0.0006619731,0.0002592556,0.0006592196,0.0003433115,0.0004368902,0.0007300935],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002462268,"about_ca_system_score_gemma":0.0004453716,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001930177,"about_ca_topic_score_gemma":0.002223183,"domain_scores_codex":[0.9995926,0.00004059427,0.0000238633,0.0001024637,0.000205873,0.00003458659],"domain_scores_gemma":[0.9997295,0.00005862226,0.00002935666,0.00005213117,0.0001174965,0.0000129549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003102559,0.0001189131,0.0009279292,0.0000871282,0.00003618833,0.0001206066,0.0000504881,0.02266708,0.3161688,0.003123003,0.002815502,0.6535742],"study_design_scores_gemma":[0.00004258193,0.0003105301,0.003757212,0.00001316751,0.0000471321,0.0009274067,0.00004313682,0.7046816,0.2807564,0.001311634,0.008055097,0.00005412046],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06631729,0.000708696,0.9282746,0.0001233556,0.0001366292,0.00008724199,0.00009757296,0.001418102,0.002836363],"genre_scores_gemma":[0.4571651,0.0006197368,0.5329858,0.0001349328,0.00008505942,0.0001214597,0.0004995993,0.000138401,0.008249912],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001930177,"threshold_uncertainty_score":0.005757391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01087108710243183,"score_gpt":0.1975140228717637,"score_spread":0.1866429357693319,"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."}}