{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008998897,0.0001019213,0.0001065389,0.0006499303,0.00061577,0.0001221114,0.0001990435,0.0001276474,0.00005320272],"category_scores_gemma":[0.0001406197,0.00007287756,0.000009203756,0.001388631,0.0008579909,0.000131093,0.0000168251,0.0004650229,0.00008660454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002629633,"about_ca_system_score_gemma":0.0002145571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001283342,"about_ca_topic_score_gemma":0.001141991,"domain_scores_codex":[0.9983699,0.00004462647,0.0000914044,0.0004524863,0.000333416,0.0007081571],"domain_scores_gemma":[0.9993857,0.0001435596,0.00002847726,0.0002170652,0.000129771,0.00009549277],"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":[0.00001483799,0.00001085838,0.0004553722,0.000001691305,0.000001688381,0.000001662098,0.00001774811,0.00002894352,0.003310553,0.0001395533,0.00004469195,0.9959724],"study_design_scores_gemma":[0.00053503,0.004464389,0.03913141,0.00001825028,0.000003843799,0.00004861719,0.0005546157,0.9096428,0.03623977,0.003546326,0.005592691,0.0002222412],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948139,0.0002052788,0.0001483123,0.002346883,0.00007679127,0.0002547913,0.000001957957,0.00008245259,0.002069617],"genre_scores_gemma":[0.9992834,0.00009138473,0.0002522365,0.0002028085,0.00002627303,0.000001869752,0.000001694499,0.000002547536,0.0001377852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9957501,"threshold_uncertainty_score":0.4736067,"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."}}