The Multimedia Computing (MMC) Group conducts research on new methodological and algorithmic concepts for analyzing, interpreting, enriching, modeling, searching and recommending multimedia data available in stand-alone collections or connected in (complex) networked data structures. Learn more about the MMC Group’s research domain and expertise, impact, and research philosophy.
The work being carried out in the MMC Group encompasses a broad palette of research directions in the domains of multimodal analysis and processing, network data computing and multimedia information systems, with a strong influx of the expertise from the domain of human factors. Learn more about the MMC Group’s research themes.
10 augustus 2020
Graph Signal Processing: Connections to Distributed Optimization and Deep Learning
Graph Signal Processing: Connections to Distributed Optimization and Deep Learning. A tutorial by Elvin Isufi at the International Conference on Signal Processing and Communications July 19 - 23, 2020
01 maart 2020
Graph-Time Spectral Analysis for Atrial Fibrillation
Atrial fibrillation is a clinical arrhythmia with multifactorial mechanisms still unresolved. Time- frequency analysis of epicardial electrograms has been investigated to study atrial fibrillation. How- ever, deeper understanding of atrial fibrillation can be achieved if the spatial dimension can be in- corporated. Unfortunately, the physical models describing the spatial relations of atrial fibrillation signals are complex and non-linear; hence, the conventional signal processing techniques to study electrograms in the joint space, time, and frequency domain are less suitable. In this study, we wish to put forward a radically different approach to analyze atrial fibrillation with a higher-level model.