{"id":"W2142196641","doi":"10.1109/icsmc.1993.384944","title":"Textured image segmentation using autoregressive model and artificial neural network","year":2002,"lang":"en","type":"article","venue":"","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Autoregressive model; Artificial intelligence; Segmentation; Artificial neural network; Image segmentation; Computer science; Pattern recognition (psychology); Image (mathematics); Image texture; Texture (cosmology); Computer vision; Identification (biology); Scale-space segmentation; 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":[0.0004721633,0.0004263322,0.000685316,0.001016631,0.0001934382,0.0006565602,0.0005664455,0.0006893494,0.0009696577],"category_scores_gemma":[0.001170843,0.0004310398,0.0008386992,0.0008522308,0.0003643045,0.0009047536,0.000324153,0.0005347255,0.0004414271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006733246,"about_ca_system_score_gemma":0.0004337691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004683689,"about_ca_topic_score_gemma":0.004750012,"domain_scores_codex":[0.9997091,0.00006184938,0.00001575485,0.00007781488,0.0001106662,0.00002476856],"domain_scores_gemma":[0.9997174,0.000147639,0.00004277122,0.00002988813,0.00005333127,0.000008816346],"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":[0.0001548856,0.00003728989,0.0007755366,0.0001804287,0.000113294,0.0002189914,0.0001282463,0.5718272,0.08690342,0.01041993,0.001340769,0.3279],"study_design_scores_gemma":[0.000002845935,0.00001272022,0.0002501241,0.000005017826,0.000009725242,0.00003585116,0.000005485071,0.9929895,0.004134645,0.001678523,0.0008673422,0.000008228698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007469883,0.0003171049,0.990905,0.00006016857,0.00001818389,0.00001364313,0.00002468548,0.0006487264,0.0005426907],"genre_scores_gemma":[0.2017969,0.0008390435,0.7935808,0.00007493934,0.00006370618,0.00008721465,0.0001897062,0.000227095,0.003140627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004683689,"threshold_uncertainty_score":0.009312868,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04706500682278777,"score_gpt":0.299171820092632,"score_spread":0.2521068132698443,"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."}}