Seminar course: Machine Learning for Remote Sensing Data Analysis
In this seminar, students will review the current state of
the art in the field of machine learning applied to remote sensing image
analysis in the framework of different Earth observation applications.
The general topics include but are not limited to:
- feature selection and extraction;
- supervised, unsupervised, semi-supervised, self-supervised image classification;
- active learning, transfer learning and domain adaptation with applications to remote sensing image analysis.
- Trainer/in: Tom Oswald Burgert
- Trainer/in: Baris Büyüktas
- Trainer/in: Kai Norman Clasen
- Trainer/in: Begüm Demir
- Trainer/in: Martin Hermann Paul Fuchs
- Trainer/in: Leonard Wayne Hackel
- Trainer/in: Genc Hoxha
- Trainer/in: Gencer Sümbül