Learning Results and their relation with course contents
- To learn digital images and the spatial filtering operation over images.
- To know basic concepts of Machine Learning: loss functions, regularization, hyperparameters, data augmentation, etc.
- To understand deep neural networks and their training algorithms: gradient descent and back-propagation.
- To learn Convolutional Neural Networks (CNN) and their most usual processing blocks/layers.
- To understand, design and train CNN architectures for image classification.
- To understand, design and train advanced CNN architectures to address other task of visual recognition: object detection, image captioning, image segmentation, image synthesis, etc.