{"id":"W1606932326","doi":"10.1007/11539506_55","title":"Fuzzy Sets Theory Based Region Merging for Robust Image Segmentation","year":2005,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Weighting; Computer science; Artificial intelligence; Pattern recognition (psychology); Similarity (geometry); Image segmentation; Fuzzy set; Fuzzy logic; Image (mathematics); Segmentation; Data mining","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":[0.001258904,0.0006597863,0.001416321,0.001753684,0.0005547997,0.00130225,0.001996987,0.001284954,0.002190097],"category_scores_gemma":[0.001915234,0.0007870375,0.001564238,0.001345103,0.0009044313,0.001553164,0.00107112,0.001082537,0.0007269636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068709,"about_ca_system_score_gemma":0.0006985522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002181547,"about_ca_topic_score_gemma":0.001884169,"domain_scores_codex":[0.9989666,0.0001493328,0.00006227059,0.0002160739,0.000539349,0.00006634235],"domain_scores_gemma":[0.9993844,0.0002749915,0.000065728,0.00007739172,0.0001832254,0.0000141476],"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":[0.0004043236,0.00009557109,0.0003592366,0.0005725861,0.0002648646,0.0002215501,0.0003098903,0.2014315,0.1629183,0.03818016,0.003679751,0.5915623],"study_design_scores_gemma":[0.0000249654,0.0001108128,0.0005381748,0.00004219374,0.0001116853,0.0002778776,0.00004281678,0.9223542,0.05403592,0.01707105,0.005339994,0.000050233],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003016031,0.000398187,0.995499,0.00002918536,0.00002544015,0.00003245904,0.00001593705,0.0001960957,0.0007877098],"genre_scores_gemma":[0.1086221,0.000611746,0.8879222,0.00006859301,0.00007014001,0.0001169173,0.0001154965,0.000139125,0.002333695],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002190097,"threshold_uncertainty_score":0.007754087,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02403247238436688,"score_gpt":0.2843533384600191,"score_spread":0.2603208660756522,"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."}}