Displaying 266 resources
Symbolic, Statistical, and Causal Representations
In machine learning, we use data to automatically find dependencies in the world, with the goal of predicting future observations.
Shape Description
This lecture overviews Shape Description that has many applications in object recognition and image compression. It covers the following topics in detail: Chain Codes. Polygonal Contour Approximations. Fourier Descriptors. Quadtrees.
Neural SLAM
This lecture overviews Neural SLAM that has many applications in robotic and autonomous vehicle localization and mapping.
Introduction to Tropical Geometry and its Applications to Machine Learning
Tropical geometry is a relatively recent field in mathematics and computer science combining elements of algebraic geometry and polyhedral geometry.
Mathematical Morphology
This lecture overviews Mathematical Morphology that has many applications in digital image processing, analysis and computer vision.
Image Typology
This lecture overviews various digital image types: 2D images, 3D images (videos, medical volumes, hyperspectral images). Multichannel images, e.g., colour and multispectral images come next. RGBD images and graphics texture images.