{"id":"W2146779595","doi":"10.1109/smi.2002.1003554","title":"Shape matching of 3D contours using normalized Fourier descriptors","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Normalization (sociology); Fourier transform; Algorithm; Smoothing; Mathematics; Fourier series; Vertex (graph theory); Eigenvalues and eigenvectors; Artificial intelligence; Mathematical analysis; Computer vision; Computer science; Combinatorics; Physics; Graph","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":[0.001112868,0.0005316328,0.0009354852,0.002871724,0.0004915044,0.001753076,0.001257049,0.00113072,0.002225026],"category_scores_gemma":[0.004261283,0.0005673838,0.0009127755,0.001480287,0.0008780211,0.0026685,0.00148848,0.0008166502,0.001424755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006303868,"about_ca_system_score_gemma":0.0008130097,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001186314,"about_ca_topic_score_gemma":0.001163532,"domain_scores_codex":[0.9991909,0.0001147176,0.00005546736,0.0001967239,0.0003814414,0.0000607928],"domain_scores_gemma":[0.9988971,0.0003629648,0.0001373671,0.0002849052,0.0002654314,0.00005222385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001869774,0.00009019019,0.0008872754,0.0001097576,0.00004393038,0.0001119241,0.0001702338,0.04667252,0.07820864,0.03448676,0.001656803,0.837375],"study_design_scores_gemma":[0.00003785216,0.0001373496,0.00164143,0.00003382136,0.00002645058,0.0005695267,0.0001322798,0.8725045,0.05557469,0.05900365,0.01025363,0.00008489635],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006645788,0.00005983197,0.9923421,0.00003147846,0.00001948588,0.00003088563,0.00002563927,0.0004532982,0.0003914492],"genre_scores_gemma":[0.07998098,0.0001447591,0.9184186,0.00005559376,0.00002653008,0.00006564705,0.0002099688,0.0002169494,0.0008809437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002871724,"threshold_uncertainty_score":0.007443428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03057872740093433,"score_gpt":0.2892067286505099,"score_spread":0.2586280012495756,"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."}}