Ementas dos Minicursos
Mini-course 1: Machine Learning I applied to Remote Sensing Imagery
Dr. Franz Rottensteiner – Leibniz University Hannover
- Generative classifiers
- Logistic Regression
- SV and Randon Forest
- Graphical Models (Markov and Conditional Random Fields)
Mini-course 2: Photogrammetry applied to environmental studies
Dr. Anette Eltner – TU Dresden
Mini-course 3: Machine Learning II applied to Remote Sensing Imagery
Dr. Farid Melgani – University of Trento
- Artificial Neural Networks
Introduction. Artificial Neuron. Multilayer Perceptron. Radial Basis Function. Probabilistic Neural Network.
Regression with Neural Networks. Deep Learning. Autoencoder. Convolutional Neural Network.
- Support Vector Machines
Introduction. Kernel Representation. Generalization Theory. VC Dimension. Structural Risk Minimization.
Margin-Based Bounds. Generalization for Regression. Maximal Margin Classification. Soft Margin
Classification. Multiclass Support Vector Machines. Support Vector Regression.