{"id":"W2036733311","doi":"10.1109/wisp.2007.4447575","title":"A Genetic Programming Approach for Classification of Textures Based on Wavelet Analysis","year":2007,"lang":"en","type":"article","venue":"","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Pattern recognition (psychology); Artificial intelligence; Genetic programming; Computer science; Wavelet; Contextual image classification; Majority rule; Class (philosophy); Energy (signal processing); Set (abstract data type); Texture (cosmology); Wavelet transform; Image (mathematics); 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":[0.0007701886,0.0006624666,0.0008563317,0.001106757,0.0003478603,0.0007008918,0.001129653,0.0009377482,0.0008278969],"category_scores_gemma":[0.001926709,0.0003458259,0.0008811149,0.0007750124,0.0006041552,0.0006124417,0.0004228436,0.001025467,0.0002051019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004890353,"about_ca_system_score_gemma":0.0005275154,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002667061,"about_ca_topic_score_gemma":0.001857973,"domain_scores_codex":[0.9995976,0.00009618299,0.00002487791,0.0001000671,0.0001453068,0.00003598403],"domain_scores_gemma":[0.999468,0.0003127944,0.00005889953,0.00003200776,0.0001080882,0.00002027809],"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":[0.00006068303,0.0001788434,0.00247923,0.0001331108,0.000152477,0.0001838331,0.000155128,0.6377293,0.016441,0.01590228,0.000980307,0.3256038],"study_design_scores_gemma":[0.000007595809,0.00003387284,0.0002290923,0.000008342833,0.00001688025,0.0000416367,0.00001195433,0.9931707,0.001775073,0.004150541,0.0005456844,0.000008742489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0145558,0.0001408533,0.9837959,0.0001249949,0.000031378,0.0000480622,0.00002178299,0.0001945172,0.001086779],"genre_scores_gemma":[0.2489324,0.0003579775,0.7478634,0.000202231,0.0000653213,0.000324454,0.000142662,0.00007592696,0.002035622],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002667061,"threshold_uncertainty_score":0.005303085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02424639772095961,"score_gpt":0.275863952962709,"score_spread":0.2516175552417494,"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."}}