Objective: Global (inter-patient) ECG classification for arrhythmia detection over
Electrocardiogram (ECG) signal is a challenging task for both humans and machines …

Objective: ECG recordings often suffer from a set of artifacts with varying types, severities,
and durations, and this makes an accurate diagnosis by machines or medical doctors …

Abstract Background and Motivations Physiological signals, such as the
Photoplethysmogram (PPG) collected through wearable devices, consistently encounter …

Robust and real-time detection of faults has become an ultimate objective for predictive
maintenance on rotating machinery. Vibration-based deep learning (DL) methodologies …

Facing enormous data generated at the network edge, Edge Intelligence (EI) emerges as
the fusion of Edge Computing and Artificial Intelligence, revolutionizing edge data …

Objective: Despite numerous studies proposed for audio restoration in the literature, most of
them focus on an isolated restoration problem such as denoising or dereverberation …

Discovering deep learning-based computer vision solutions for use with constrained devices
is exceptionally hard, and the trade-offs are often too undermining. Deep learning models …

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 …

Convolutional neural networks (CNN) are built upon the classical McCulloch-Pitts neuron
model, which is essentially a linear model, where the nonlinearity is provided by a separate …

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 …