Possibilities of convolutional neural networks use for remote sensing image classification
In recent years, the speed of technological progress in certain science fields is getting faster and faster. It is making it hard for other scientific areas to keep up with this tempo. One of the exemplary relationships is the link between artificial and convolutional neural network structures and the province of geomatics or remote sensing. New architectures of artificial neural network models are being published with an expeditious tempo and the common approach of the remote sensing researchers is to use the most recent structures, without the basic understanding of the background or relative performance. The goal of this thesis is to perform systematic research on the possibilities of use of chosen convolutional neural network architectures on various selected use cases from the field of remote sensing.
Ing. Ondřej Pešek
- Prof. Aleš Čepek, CSc.
- Ing. Martin Landa, Ph.D.
- Professional debate: Ing. Lukáš Brodský, Ph.D.
- The final text: Would be nice to finish it firstly
Hopefully one day.
