Lectures related to Automatic Vectorization: Principles and Applications

Explores neighborhood averaging, Gaussian smoothing, median filtering, contrast enhancement, and edge detection in image processing.

Covers the practical use of QGIS for spatial data analysis and visualization, including georeferencing historical maps and manipulating vector data.

Covers discrete variables in geographic information systems and their geometric properties, including spatial arrangement and autocorrelation.

Introduces image processing basics in Python, covering manipulation, grayscale conversion, edge detection, and convolution with kernels.

Explores classic image filters like Moving Average, Gaussian Blur, Sobel filter, and Laplacian operator.

Explores the calculation of correlation energy and CSF's in electronic structure calculations.