Data is the fuel of machine learning algorithms, therefore data generation in machine
learning is becoming an important topic. The problem is that finding enough data for …

Recent years have witnessed a surge in the popularity of Machine Learning (ML), applied
across diverse domains. However, progress is impeded by the scarcity of training data due …

Recent approaches for surgical activity localization rely on motion features derived from the
optical flow (OF). However, although they consider state-of-the-art CNNs when computing …

In recent intelligent-robot-assisted surgery studies, an urgent issue is how to detect the
motion of instruments and soft tissue accurately from intra-operative images. Although …

Camouflaged object detection is paramount across diverse domains, spanning military
surveillance, wildlife conservation, and security systems. Despite the efficiency of deep …

Abstract Machine learning-based solutions rely heavily on the quality and quantity of the
training data. In the medical domain, the main challenge is to acquire rich and diverse …

Sustained delivery of regenerative retinal therapies by robotic systems requires intra-
operative tracking of the retinal fundus. This thesis presents a supervised convolutional …