{"id":"W2135921972","doi":"10.5430/jbgc.v3n1p6","title":"Non-uniform illumination correction in infrared images based on a modified fuzzy c-means algorithm","year":2012,"lang":"en","type":"article","venue":"Journal of Biomedical Graphics and Computing","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Normalization (sociology); Brightness; Shading; Artificial intelligence; Pixel; Algorithm; Computer science; Color constancy; Computer vision; Multiplicative function; Mathematics; Image (mathematics); Optics; Computer graphics (images); Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001059385,0.000837163,0.001050791,0.001463159,0.0008378827,0.001024013,0.001889058,0.001240665,0.0009804392],"category_scores_gemma":[0.002415128,0.0004534735,0.001278005,0.001290035,0.0005782719,0.0008911247,0.0005939654,0.001027265,0.0003468174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001242125,"about_ca_system_score_gemma":0.00189159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01924756,"about_ca_topic_score_gemma":0.0157685,"domain_scores_codex":[0.9989957,0.0001055037,0.00006328009,0.0002737032,0.0004840204,0.00007780911],"domain_scores_gemma":[0.9991512,0.0002059288,0.00008667456,0.00006682397,0.0004619547,0.0000274198],"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":[0.0003058568,0.0001110584,0.0009382144,0.000223478,0.0001439529,0.0001553611,0.0002731662,0.2307975,0.05648291,0.004781292,0.001922319,0.703865],"study_design_scores_gemma":[0.00001210598,0.00003874541,0.0006106905,0.00001304928,0.00002740961,0.00006942236,0.00001647406,0.9867098,0.0103622,0.0009319141,0.001182321,0.00002582931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009137078,0.0002008372,0.9896163,0.00004653296,0.00003958043,0.00006087052,0.00001606645,0.0003900941,0.0004925963],"genre_scores_gemma":[0.1170858,0.0002598874,0.8808359,0.00006279183,0.00003904356,0.0001669659,0.0000861653,0.00009053449,0.001372941],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01924756,"threshold_uncertainty_score":0.03827107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186440386362863,"score_gpt":0.2698766518422326,"score_spread":0.2580122479786039,"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."}}