{"id":"W2038216307","doi":"10.1109/icdsp.2011.6004888","title":"Face detection in a compressed domain","year":2011,"lang":"en","type":"preprint","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Discrete cosine transform; Computer science; Lapped transform; Transform coding; Artificial intelligence; Image (mathematics); Computer vision; Face (sociological concept); Focus (optics); Algorithm; Merge (version control); Image compression; Image processing; 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":[0.0002580781,0.0002859702,0.0003381094,0.0003340344,0.00004364691,0.0001171407,0.002646566,0.0002987201,0.00004003166],"category_scores_gemma":[0.00002625537,0.0002657369,0.00007642565,0.0002431321,0.00003991213,0.0004487993,0.005598368,0.0007807335,0.00004807694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001005177,"about_ca_system_score_gemma":0.00005670241,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003182197,"about_ca_topic_score_gemma":0.000126495,"domain_scores_codex":[0.9980048,0.0001487031,0.0003942134,0.0009030508,0.0002558067,0.0002934164],"domain_scores_gemma":[0.9975616,0.00006183884,0.0002089694,0.002031672,0.00005402945,0.00008186453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001050257,0.0009592695,0.0002586662,0.0004551995,0.00007097082,0.0002498319,0.004828382,0.003794775,0.05119338,0.2045355,0.006809868,0.7267392],"study_design_scores_gemma":[0.0003554137,0.00005524361,0.0009167136,0.0002684722,0.000002760566,0.00001249709,0.000029382,0.06154749,0.2856231,0.6434427,0.006999189,0.0007470218],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001409406,0.000102696,0.987694,0.00009017041,0.0004325036,0.0005382094,0.000006841527,0.001322324,0.008403815],"genre_scores_gemma":[0.418595,0.00004128235,0.5808311,0.0001288159,0.00002433337,0.0001895383,0.000009422067,0.00001643969,0.0001641642],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7259921,"threshold_uncertainty_score":0.9999795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0312546934832722,"score_gpt":0.283949193130116,"score_spread":0.2526944996468438,"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."}}