activity
20192022
most citedA Review of Vibration-Based Damage Detection in Civil Structures: From Traditional Methods to Machine Learning and Deep Learning Applications

1.4k citations · 1.4k across the 11 of their papers we have counts for

collaborators

16 papers

cs.LG20222 cited

Global ECG Classification by Self-Operational Neural Networks with Feature Injection

Muhammad Uzair Zahid, Serkan Kiranyaz, Moncef Gabbouj

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

cs.RO20222 cited

OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics

N. Passalis, S. Pedrazzi, R. Babuska +15

Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their r…

cs.LG2022

Non-Linear Spectral Dimensionality Reduction Under Uncertainty

Firas Laakom, Jenni Raitoharju, Nikolaos Passalis +2

In this paper, we consider the problem of non-linear dimensionality reduction under uncertainty, both from a theoretical and algorithmic perspectives. Since real-world data usually…

eess.SP2022

Blind ECG Restoration by Operational Cycle-GANs

Serkan Kiranyaz, Ozer Can Devecioglu, Turker Ince +8

Continuous long-term monitoring of electrocardiography (ECG) signals is crucial for the early detection of cardiac abnormalities such as arrhythmia. Non-clinical ECG recordings acq…

cs.CV20223 cited

Self-attention fusion for audiovisual emotion recognition with incomplete data

Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj

In this paper, we consider the problem of multimodal data analysis with a use case of audiovisual emotion recognition. We propose an architecture capable of learning from raw data…

cs.CV2022

Self-Attention Neural Bag-of-Features

Kateryna Chumachenko, Alexandros Iosifidis, Moncef Gabbouj

In this work, we propose several attention formulations for multivariate sequence data. We build on top of the recently introduced 2D-Attention and reformulate the attention learni…