Informations du cours

Recent advances in satellite technology have led to a regular, frequent, and high-resolution monitoring of Earth at the global scale, providing an unprecedented amount of Earth observation (EO) data. To efficiently process and analyze the large-amount EO data, remote sensing has evolved into a multidisciplinary field, where machine learning and computer vision algorithms play an important role nowadays.

Participants of this project course gain practical experience in applying computer vision techniques to address Earth observation questions in a collaborative team and acquire knowledge on state-of-the-art topics in the field of computer vision for remote sensing. The general topics include but are not limited to: i) feature extraction and learning; ii) classification and retrieval of satellite images; iii) change detection and analysis of image time series; iv) super-resolution in the spectral and spatial domain; v) target detection and object recognition; vi) multi-sensor and multi-source data fusion; and vii) estimation of biophysical parameters.