Minimum error entropy with fiducial points (MEEF) has received a lot of attention, due to its
outstanding performance to curb the negative influence caused by non-Gaussian noises in …

In this work, we propose a novel approach called Operational Support Estimator Networks
(OSENs) for the support estimation task. Support Estimation (SE) is defined as finding the …

Multi-modal 3D object detection is instrumental in identifying and localizing objects within
3D space. It combines RGB images from cameras and point-clouds data from lidar sensors …

Strong perception, precise distance estimate, and dependable object tracking are necessary
for autonomous vehicle systems to function. To improve autonomous driving capabilities, we …

The ability of a robot to perceive and understand its environment is crucial for its actions and
behavior. Humans are adept at using semantic information for object localization and path …

Visual object tracking, crucial in aerial applications such as surveillance, cinematography,
and chasing, faces challenges despite AI advancements. Current solutions lack full …

LiDAR point clouds can effectively depict the motion and posture of objects in three-
dimensional space. Many studies accomplish the 3D object detection by voxelizing point …

The continually evolving image segmentation methods in computer vision can further
broaden the cognitive abilities of the robot. As humans, we won't judge if the object is …

This dissertation investigates the analysis of linear systems of equations, particularly
focusing on underdetermined systems where the solution vector is sparse or approximately …

The research outlined in this thesis was carried out at Tampere University, Finland, between
the years 2020 and 2023. I greatly acknowledge the acquired funding from the National …