How effective are minimax methods in mitigating sample selection bias?

Sample selection bias is a well-known problem in machine learning, where the source and target data distributions differ, leading to biased predictions and difficulties in generalization. This bias presents significant challenges for modern machine learning algorithms. To tackle this problem, researchers have focused on developing domain...

Model-specific Explainable Artificial Intelligence techniques: State-of-the-art, Advantages and Limitations

Artificial Intelligence (AI) and Machine learning (ML) applications are being widely used to solve different problems in different sectors. These applications have enabled the human-effort and involvement to be very low. The AI/ML systems<br/>make their own predictions and do not require a great deal of human help. However, over the last few...

Partial Least Squares on Hyperspectral data: A data-driven approach for predicting the growth of potato plants

The potato is a plant that can grow from another potato tuber. Farmers and producers have to contend with the declining quality of soil and are producing less vital potato tubers. The differences in emergence speed between batches of the same variety of potato tubers cannot be explained. This is why Project ‘Flight to Vitality’ (FtV) is...

Heart rate monitoring using PPG signals

This bachelor’s thesis discusses the idea and implementation of real-time heart rate monitoring using photo- plethysmography (PPG) signals. PPG signals measured from the wrist are often subjected to distortion and noise. Signal processing techniques that tackle these issues were investigated and implemented. The algo- rithm of choice was JOSS....