{"id":"W1553738992","doi":"10.1007/978-3-642-19315-6_30","title":"Compressed Sensing for Robust Texture Classification","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Texture (cosmology); Artificial intelligence; Computer science; Pattern recognition (psychology); Compressed sensing; Computer vision; Image (mathematics)","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":[0.0002739661,0.0006290984,0.0006736491,0.0008253154,0.0001959273,0.0007325145,0.0007118379,0.0007685251,0.008716756],"category_scores_gemma":[0.001285411,0.000256234,0.0004136606,0.001340445,0.0005643048,0.0007863273,0.0006709258,0.001033921,0.002071257],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000290333,"about_ca_system_score_gemma":0.0003104989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001436625,"about_ca_topic_score_gemma":0.001945796,"domain_scores_codex":[0.9996951,0.00004063024,0.0000131635,0.00004290164,0.0001872963,0.00002102272],"domain_scores_gemma":[0.9995408,0.0002472691,0.00003097968,0.00009214137,0.00007628713,0.00001253073],"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":[0.0001252675,0.00004532817,0.00009804068,0.0002860089,0.00003549163,0.00007892514,0.00004290324,0.02436491,0.05046167,0.02930951,0.01925089,0.875901],"study_design_scores_gemma":[0.00003654588,0.0001217031,0.0008859435,0.0001059635,0.0000501392,0.0005722395,0.00004703364,0.8536852,0.0467159,0.05632983,0.04140255,0.00004695525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004270665,0.003659112,0.9840242,0.0005178521,0.0003011168,0.00004169649,0.0003124801,0.000785005,0.006087845],"genre_scores_gemma":[0.1232066,0.006832781,0.8478739,0.0006426322,0.001034496,0.0001596052,0.001350939,0.0003902688,0.01850869],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008716756,"threshold_uncertainty_score":0.0291605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05823035430574065,"score_gpt":0.2846098010811666,"score_spread":0.2263794467754259,"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."}}