{"id":"W2143812340","doi":"10.1109/cccrv.2004.1301422","title":"Simultaneous segmentation of range and color images based on Bayesian decision theory","year":2004,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Classification of discontinuities; Parametric statistics; Artificial intelligence; Range (aeronautics); Bayesian probability; Segmentation; Computer science; Image segmentation; Algorithm; Parametric model; Limit (mathematics); Pattern recognition (psychology); Partition (number theory); Computer vision; Mathematics; Statistics","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":[0.002321653,0.0008882517,0.00134553,0.001839163,0.0006135579,0.00180904,0.001590912,0.001347627,0.001692894],"category_scores_gemma":[0.005013713,0.0009685908,0.001392662,0.001096024,0.001366612,0.002469481,0.001469109,0.001378963,0.001070512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001295379,"about_ca_system_score_gemma":0.001436658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003569629,"about_ca_topic_score_gemma":0.004136266,"domain_scores_codex":[0.9980205,0.0004821945,0.0001144671,0.0004487104,0.0007796101,0.0001545245],"domain_scores_gemma":[0.9979939,0.001175067,0.0001943588,0.0002006103,0.0003583274,0.00007764596],"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":[0.0004441566,0.0001178342,0.001211022,0.0002089271,0.0001560974,0.0001629272,0.0004439414,0.2133276,0.05223127,0.04891814,0.00210257,0.6806756],"study_design_scores_gemma":[0.00003274064,0.0000742484,0.0008140947,0.00003082979,0.00004776847,0.000172467,0.00004154691,0.9412322,0.01468312,0.03850529,0.004309256,0.00005648289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001566169,0.0000829063,0.9978195,0.00002862442,0.000007045913,0.00001873876,0.000009567492,0.0001444949,0.0003229523],"genre_scores_gemma":[0.0475926,0.0001877362,0.9509364,0.00006878222,0.00003034607,0.00008435745,0.0001001235,0.0001411889,0.0008585845],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003569629,"threshold_uncertainty_score":0.01227826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00590735897034707,"score_gpt":0.2704431987013455,"score_spread":0.2645358397309985,"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."}}