Pattern Recognition University course KPI IPT 2019y All needed tasks described in all-labs.pdf Solutions described in solved-tasks.pdf lab1 - Bayesian Strategy for Binary and Delta Loss Function Image Denoising (Bernoulli noise) lab2.1 - Analysis of Nonbayesian Strategy lab2.2 - Implementation of Effective algorithm for calculation cumulative sums of 1D, 2D and 3D arrays lab3 - Hidden Markov Model (HMM) Divisibility sum of digits lab4 - DP algorithm for chain-structured graphical models Binocular stereo vision NOTE: Source of images - http://vision.middlebury.edu/stereo/data/ lab5 - EM Algorithm for Binary Clustering Binary image clustering (mnist dataset) lab6 - Modification of a Perceptron Algorithm Modification of Perceptron Algorithm where hyperplane is a circle (modified scalar product)
