Convolutional neural networks raised the bar for machine learning and artificial intelligence
applications, mainly due to the abundance of data and computations. However, there is not …

Detecting objects with a small representation in images is a challenging task, especially
when the style of the images is very different from recent photos, which is the case for …

The biggest fear when deploying machine learning models to the real world is their ability to
handle the new data. This problem is significant especially in medicine, where models …

Image classification models have improved drastically due to neural networks. But as a
direct consequence of being trained on a specific dataset, neural networks tend to be biased …

Human activity recognition (HAR) is an emerging field of study to recognize human
movement and actions from recorded data. It plays a significant role in human-computer …

This thesis is at the intersection of musicology and artificial intelligence, aiming to leverage
AI to help musicologists with repetitive work, such as object searching in the museum's …

We apply augmentations to our dataset to enhance the quality of our predictions and make
our final models more resilient to noisy data and domain drifts. Yet the question remains …

Cerebral palsy is the most common physical disability during childhood. Cerebral palsy
related hip disease is caused by an imbalance of muscle forces, resulting in progressive …

We apply augmentations to our dataset to enhance the quality of our predictions and make
our final models more resilient to noisy data and domain drifts. Yet the question remains …