{"id":"W2137858948","doi":"10.24908/pceea.v0i0.4702","title":"INTRODUCTION TO THE FOURIER TRASNFORM: IMAGE PROCESSING LABORATORY EXAMPLE","year":2012,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Image Processing Techniques and Applications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Computer science; Signal processing; Image processing; Multidimensional signal processing; MATLAB; Session (web analytics); SIGNAL (programming language); Code (set theory); Simple (philosophy); Fourier transform; Software; Domain (mathematical analysis); Digital image processing; Subject (documents); Image (mathematics); Data processing; Algorithm; Computer engineering; Artificial intelligence; Digital signal processing; Programming language; Computer hardware; Database; Mathematics; Set (abstract data type); World Wide Web","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0006265619,0.0001504355,0.0001158468,0.0001852328,0.0002779968,0.0001673222,0.0003237833,0.0001051738,0.0000279637],"category_scores_gemma":[0.0003845938,0.0001276763,0.00004858217,0.0008970359,0.00001566519,0.0005685384,0.00002133683,0.0002491697,0.00002516135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001355924,"about_ca_system_score_gemma":0.0002483823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008814253,"about_ca_topic_score_gemma":0.0005092099,"domain_scores_codex":[0.9989745,0.000003596133,0.0002452041,0.0001296776,0.0002549403,0.0003921027],"domain_scores_gemma":[0.9989843,0.00001470747,0.0001336651,0.0001542482,0.00051393,0.0001991772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001525479,0.00006469632,0.004776678,0.0004583362,0.00005685458,1.259935e-8,0.004478746,0.001229161,0.02587364,0.006536643,0.9415931,0.01493063],"study_design_scores_gemma":[0.00006063046,0.000006075206,0.01984546,0.00007276081,0.00005092,0.000003552729,0.0003391824,0.005328447,0.02563379,0.0001080751,0.9482481,0.0003030387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6934652,0.004231677,0.02565331,0.1973667,0.01916502,0.007601497,0.0003549099,0.005285151,0.04687653],"genre_scores_gemma":[0.9814189,0.00001073695,0.01480042,0.0003839544,0.001799968,0.0003084657,0.00001004727,0.00006600031,0.001201471],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2879537,"threshold_uncertainty_score":0.5206488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005365738537235951,"score_gpt":0.2055650854174851,"score_spread":0.2001993468802492,"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."}}