{"id":"W2293276065","doi":"10.1109/icip.2015.7351041","title":"External forces for active contours using the undecimated wavelet transform","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Active contour model; Artificial intelligence; Wavelet transform; Vector flow; Convolution (computer science); Computer vision; Parametric statistics; Noise (video); Computer science; Wavelet; Sensitivity (control systems); Edge detection; Gradient descent; Pattern recognition (psychology); Mathematics; Image processing; Image (mathematics); Image segmentation; Artificial neural network; Engineering","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":[0.000836105,0.0006194828,0.0004994008,0.0006227134,0.0002738342,0.000988249,0.0008777856,0.001116702,0.002325878],"category_scores_gemma":[0.002111282,0.0003893213,0.0006545578,0.0005454916,0.0007645291,0.001724204,0.0008861109,0.001167555,0.0008480581],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003961188,"about_ca_system_score_gemma":0.0004893839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006555632,"about_ca_topic_score_gemma":0.0007269186,"domain_scores_codex":[0.9997337,0.00005598528,0.00001446622,0.00003674739,0.000144613,0.00001447236],"domain_scores_gemma":[0.9995988,0.0002107786,0.00004286479,0.00004660319,0.00008393504,0.00001702248],"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":[0.00009322643,0.00007821875,0.0003670036,0.0002437028,0.00004187654,0.0001639478,0.0002067092,0.4294488,0.05480256,0.1586314,0.00264839,0.3532741],"study_design_scores_gemma":[0.000004928298,0.0000137585,0.00005408717,0.000009468719,0.00000319189,0.00003645199,0.000006558121,0.9851646,0.003826469,0.008549785,0.002324076,0.000006622712],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001639476,0.00007227407,0.9977076,0.00003377672,0.00001339714,0.000009998213,0.000006877881,0.0000734798,0.0004430088],"genre_scores_gemma":[0.1471834,0.0005210479,0.8478904,0.00008327762,0.00007196912,0.0001373985,0.0001339451,0.0002357786,0.003742831],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002325878,"threshold_uncertainty_score":0.00778091,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08089926097888672,"score_gpt":0.3556141303533271,"score_spread":0.2747148693744404,"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."}}