{"id":"W1672651452","doi":"10.1109/iscas.2002.1009958","title":"Canny edge based image expansion","year":2003,"lang":"en","type":"article","venue":"","topic":"Advanced Image Processing Techniques","field":"Computer Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bilinear interpolation; Bicubic interpolation; Canny edge detector; Stairstep interpolation; Interpolation (computer graphics); Image gradient; Artificial intelligence; Deriche edge detector; Computer vision; Mathematics; Enhanced Data Rates for GSM Evolution; Image scaling; Pixel; Demosaicing; Edge detection; Image (mathematics); Computer science; Algorithm; Image processing; Multivariate interpolation; Binary image","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001651256,0.000096452,0.00008049153,0.00006826305,0.00008395076,0.0001107419,0.0004657012,0.00003031193,0.00004783132],"category_scores_gemma":[0.0001213517,0.00008317454,0.00002722076,0.0002868862,0.00003814973,0.000768183,0.00006703025,0.00007690202,0.00004998074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003440803,"about_ca_system_score_gemma":0.0001166983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006769708,"about_ca_topic_score_gemma":0.000001727788,"domain_scores_codex":[0.9992172,0.00003731509,0.0001113081,0.0002822002,0.0001451251,0.0002068515],"domain_scores_gemma":[0.9992616,0.00003213761,0.00003707887,0.0005109982,0.00009416048,0.00006403678],"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":[0.000005301717,0.0002394211,0.0002674994,0.00005634319,0.000005320986,0.00008836513,0.0003023292,0.00001286078,0.6175336,0.252694,0.0292133,0.09958163],"study_design_scores_gemma":[0.0001905453,0.00004207476,0.00006130392,0.00001870023,0.000001356475,0.00001240273,0.000007473816,0.0404724,0.896593,0.0404386,0.02192592,0.0002362052],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001190888,0.00005883033,0.964197,0.000447021,0.00007967279,0.00006816754,2.022378e-7,0.0009545013,0.03407548],"genre_scores_gemma":[0.06389062,0.000001905383,0.9342737,0.001010768,0.000007555962,0.00001354838,3.623452e-7,0.000008098411,0.0007934979],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2790594,"threshold_uncertainty_score":0.3391759,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01209584733312898,"score_gpt":0.2691881410219382,"score_spread":0.2570922936888093,"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."}}