Available Theses
- Curiosity-driven Reinforcement Learning for intelligent control
- Robust multi-object real-time tracking by deep neural networks
- Camera-LiDAR sensor fusion for autonomous driving
- Visual-based control of a quadruped robot dog
- Realistic virtual environments for automatic dataset generation
- Deep learning for anomaly detection in railway environments
- Thrustworthy AI for safety-critical systems
- FPGA acceleration of deep neural networks
- Deep neural networks for complex chords recognition
- Learning jazz improvisation by deep neural networks
To know more details on the theses please contact me via Email for an appointment.
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