Computational Perpeception Course
Master in Computing from Escuela Politécnica Nacional
Marco E. Benalcázar, Ph.D.
Lectures
Introduction to Computational Perception
Ver
Human Perception vs. Computational Perception
Ver
Image Acquisition and Representation
Ver
Image Acquisition and Representation
Ver
Concepts and Operations for Images
Ver
Concepts and Operations for Images
Ver
Binary Mathematical Morphology
Ver
Binary Mathematical Morphology
Ver
Derivatives, Convolution and Correlation of Images
Ver
Discrete 2D Fourier Transform
Ver
Motion Estimation and Compensation
Ver
Machine Learning Applied to Computational Perception
Ver
Machine Learning Fundamentals
(Probability and Hoeffding Inequality)
Ver
Machine Learning Fundamentals
(Probability and Hoeffding Inequality) Fundamentals of Machine Learning
(Vapnik-Chervonenkis Generalization Theory)
Ver
Probabilistic Design of Classifiers: The Classifier and Bayes Error
Ver
Bias Balance Analysis - Variance
Ver
No Free Lunch (NFL) theorems for Machine Learning
Ver
Estimation of Error for Classification
Ver
Artificial Neural Networks (Feed-Forward)
Ver
Error Back-propagation Algorithm
Ver
Practical Tips for Artificial Neural Networks
Ver
Matlab Library of Feed-Forward Neural Networks
Ver
Introduction to Deep Learning
Ver
Architecture of Convolutional Neural Networks (CNNs)
Ver
Convolutional Neural Networks Training
Ver
