{"id":"W2350882315","doi":"","title":"Research on Face Detection Based on Skin Color and Improved Adaboost Algorithm","year":2013,"lang":"en","type":"article","venue":"Electronic Science and Technology","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec","funders":"","keywords":"Face detection; AdaBoost; Artificial intelligence; Computer science; Face (sociological concept); Color space; YCbCr; Pattern recognition (psychology); Feature (linguistics); Computer vision; Facial recognition system; Mathematics; Algorithm; Color image; Support vector machine; Image processing; 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":[0.001127356,0.0008972971,0.00134432,0.001853774,0.0005299539,0.001035117,0.001515094,0.00109726,0.001539519],"category_scores_gemma":[0.001791671,0.00053524,0.001144454,0.001413281,0.000595769,0.002192586,0.0005416612,0.001105742,0.0005144655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000821724,"about_ca_system_score_gemma":0.0009119249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004839807,"about_ca_topic_score_gemma":0.002212374,"domain_scores_codex":[0.9982657,0.0002781178,0.00007457372,0.0004977988,0.0007249032,0.0001589486],"domain_scores_gemma":[0.9991125,0.0002288029,0.00005372072,0.00005835456,0.0005078186,0.00003865316],"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":[0.000227261,0.0002009746,0.00278317,0.0004016676,0.0001966589,0.0001380889,0.000140408,0.09053471,0.03594166,0.01148335,0.003551788,0.8544002],"study_design_scores_gemma":[0.00002059775,0.0001036494,0.001834134,0.00002216686,0.00006252847,0.000239893,0.00004699617,0.9719632,0.01762876,0.003469366,0.0045635,0.00004517436],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0146634,0.001805192,0.9800178,0.0001578286,0.0002277553,0.00004427572,0.00002520597,0.0007674605,0.00229104],"genre_scores_gemma":[0.4069683,0.003801414,0.5778158,0.0003461478,0.0004391592,0.0001622338,0.0001895205,0.0002132352,0.01006429],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004839807,"threshold_uncertainty_score":0.009623289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009731481868770094,"score_gpt":0.2480028641575366,"score_spread":0.2382713822887665,"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."}}