{"id":"W2138265313","doi":"10.1109/icip.2004.1421665","title":"Sar image segmentation with active contours and level sets","year":2005,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Synthetic aperture radar; Artificial intelligence; Computer vision; Computer science; Image segmentation; Scale-space segmentation; Speckle noise; Regularization (linguistics); Speckle pattern; Segmentation; Radar imaging; Inverse synthetic aperture radar; Multiplicative noise; Segmentation-based object categorization; Algorithm; Pattern recognition (psychology); Radar; Transmission (telecommunications)","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":[0.001422498,0.0008426066,0.0008533087,0.001606807,0.0003771529,0.001663239,0.001264449,0.001688175,0.001044554],"category_scores_gemma":[0.004039029,0.0009887273,0.00120925,0.001350647,0.001487384,0.002035984,0.001335113,0.001310854,0.0005353033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009530758,"about_ca_system_score_gemma":0.0006048455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001447591,"about_ca_topic_score_gemma":0.001141044,"domain_scores_codex":[0.9990636,0.0003187507,0.00006293015,0.0001383186,0.0003822893,0.00003420337],"domain_scores_gemma":[0.9987724,0.0007230468,0.0001525046,0.0001438841,0.0001783623,0.00002970547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008917163,0.00006154265,0.0004675611,0.0002094511,0.00008814334,0.0001124284,0.0002561723,0.7368615,0.02885668,0.06844637,0.001197994,0.163353],"study_design_scores_gemma":[0.000007552857,0.00002165025,0.0001169554,0.00001458455,0.000006255999,0.00004411035,0.00001081051,0.9744886,0.005507149,0.0177416,0.002026337,0.00001429794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002051097,0.0001487261,0.9970937,0.00005379931,0.000008908168,0.00002397154,0.00001042662,0.0001654973,0.0004438457],"genre_scores_gemma":[0.07440327,0.0004218927,0.9236132,0.00005630243,0.00004239001,0.0001353791,0.00009140922,0.0001549921,0.00108123],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001688175,"threshold_uncertainty_score":0.007522941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176459759948991,"score_gpt":0.2986161679703871,"score_spread":0.2768515703708972,"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."}}