{"id":"W4256196623","doi":"10.21611/qirt.2010.002","title":"A new fusion framework for multispectral IR face recognition in the texture space","year":2010,"lang":"en","type":"article","venue":"Proceedings of the 2010 International Conference on Quantitative InfraRed Thermography","topic":"Face and Expression Recognition","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Multispectral image; Artificial intelligence; Face (sociological concept); Computer vision; Computer science; Facial recognition system; Fusion; Texture (cosmology); Space (punctuation); Image texture; Pattern recognition (psychology); 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":[0.001246103,0.0007846484,0.0009843005,0.001158333,0.0004206011,0.001105589,0.00123372,0.0008108887,0.002413744],"category_scores_gemma":[0.001382055,0.0002961951,0.001402884,0.0008586432,0.0005450498,0.001761289,0.001514559,0.001092349,0.00144666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004135788,"about_ca_system_score_gemma":0.000529794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002351984,"about_ca_topic_score_gemma":0.00228083,"domain_scores_codex":[0.9989619,0.0001245206,0.00004407868,0.000190686,0.0005889292,0.0000899771],"domain_scores_gemma":[0.9995148,0.00006412469,0.00004294982,0.00009715162,0.0002441786,0.00003691647],"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":[0.0002816582,0.0001998031,0.001042214,0.0002574867,0.0002101455,0.0001830802,0.0001642127,0.08320462,0.1453584,0.03610352,0.005482926,0.727512],"study_design_scores_gemma":[0.00002064023,0.00023148,0.001827901,0.00003302151,0.0001180358,0.0004915723,0.00007524472,0.9127399,0.04573673,0.02395794,0.0146962,0.00007128117],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002291535,0.0001776145,0.9963484,0.00004358983,0.00004738436,0.00001882032,0.00004822047,0.0003249192,0.0006996057],"genre_scores_gemma":[0.1522844,0.0007048076,0.8408238,0.0002073155,0.000281792,0.0001435424,0.0006013059,0.000190185,0.004762857],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002413744,"threshold_uncertainty_score":0.00807482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04640467133581928,"score_gpt":0.3078350933265688,"score_spread":0.2614304219907496,"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."}}