{"id":"W1992491299","doi":"10.1109/icassp.2013.6637889","title":"Singular point detection based on orientation filed regularization and poincaré index in fingerprint images","year":2013,"lang":"en","type":"article","venue":"","topic":"Biometric Identification and Security","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Artificial intelligence; Orientation (vector space); Fingerprint (computing); Regularization (linguistics); Pattern recognition (psychology); Singular point of a curve; Fingerprint recognition; Computer vision; Computer science; Mathematics; Spurious relationship; Helmholtz free energy; Geometry; Physics; 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":[0.0006137804,0.0003689306,0.0005503774,0.001770975,0.0002501054,0.0004113814,0.000383395,0.0003104438,0.000597158],"category_scores_gemma":[0.001459169,0.0002011863,0.0004972815,0.0009352544,0.0005710723,0.0006843562,0.0004906244,0.0004129187,0.0002819101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002365583,"about_ca_system_score_gemma":0.0003418413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000997494,"about_ca_topic_score_gemma":0.0009686388,"domain_scores_codex":[0.9995242,0.00009209733,0.00002486067,0.00008382583,0.0002332402,0.00004175969],"domain_scores_gemma":[0.9993666,0.000216794,0.00009744144,0.0001153063,0.0001580173,0.00004590813],"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":[0.0003809349,0.0001124683,0.005041674,0.0001191237,0.00008527283,0.000242606,0.0001174713,0.04523088,0.3382594,0.00946928,0.001335207,0.5996056],"study_design_scores_gemma":[0.000009495434,0.0001730951,0.008089475,0.000008919352,0.00002517904,0.0004483679,0.00003082724,0.8987017,0.08802094,0.003197024,0.001252438,0.0000426522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1000279,0.0001670939,0.898473,0.00005093261,0.0000226248,0.00002567364,0.00004020826,0.0004786799,0.0007139165],"genre_scores_gemma":[0.5087531,0.0003754561,0.4888048,0.00003766085,0.00007442433,0.00003946845,0.0002811459,0.00007126464,0.00156268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001770975,"threshold_uncertainty_score":0.003246009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009310290878172357,"score_gpt":0.225581032343445,"score_spread":0.2162707414652727,"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."}}