{"id":"W2023739648","doi":"10.1109/icices.2014.7033989","title":"Fabric quality testing using image processing","year":2014,"lang":"en","type":"article","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alpha Technologies (Canada)","funders":"","keywords":"Weaving; Textile; Artificial intelligence; Process (computing); Computer vision; Computer science; Woven fabric; Clothing; Texture (cosmology); Gabor filter; Visual inspection; Image processing; Feature extraction; Image (mathematics); Engineering; Materials science; Mechanical engineering; Composite material","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":[0.0006089308,0.0004762101,0.0003010629,0.001790879,0.000201757,0.0007277067,0.0003788217,0.0005034908,0.004411309],"category_scores_gemma":[0.001464181,0.0001578341,0.0004254034,0.0009866797,0.0002585386,0.0004903923,0.0003249547,0.0002283755,0.0009526631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002242874,"about_ca_system_score_gemma":0.0001195093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008285764,"about_ca_topic_score_gemma":0.0008605517,"domain_scores_codex":[0.9992348,0.00008344594,0.00004871135,0.0001257089,0.0004387091,0.00006866198],"domain_scores_gemma":[0.9988993,0.0002142096,0.0001618165,0.000169746,0.0005126016,0.00004227871],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008053906,0.0002743163,0.01163845,0.0004157396,0.000089648,0.0004346344,0.0001749347,0.008773527,0.6062245,0.0005434806,0.001023824,0.3696015],"study_design_scores_gemma":[0.00007254708,0.00203567,0.1267087,0.00006910341,0.0001252599,0.001652335,0.000348527,0.1772139,0.6847554,0.0006642236,0.006265608,0.00008874576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.715589,0.0006984962,0.2686481,0.0001195673,0.0001348865,0.0002373137,0.0006363927,0.002917532,0.0110187],"genre_scores_gemma":[0.9279905,0.0003115027,0.0667212,0.0000543622,0.00002902521,0.00006562344,0.000597643,0.0001771968,0.004053104],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004411309,"threshold_uncertainty_score":0.01475728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0761009398184522,"score_gpt":0.2995944848890914,"score_spread":0.2234935450706392,"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."}}