SPS Newsletter Article

Pierre Comon is currently Emeritus Research Director with CNRS. He received the Doctorate degree in 1985 from the University of Grenoble, and the Habilitation to Lead Researches in 1995, from the University of Nice, France. 

Professor Konstantinos N (Kostas) Plataniotis is the Bell Canada Endowed Chair in Multimedia and a professor with The Edward S. Rogers Sr. Department of Electrical and Computer Engineering at the University of Toronto (UofT) in Toronto, Ontario, Canada, where he directs the Multimedia Laboratory.

Prof. Nikolaos (Nikos) Sidiropoulos is the Louis T. Rader Professor of Electrical and Computer Engineering at the University of Virginia. He earned his Ph.D. in Electrical Engineering from the University of Maryland–College Park, in 1992.

Verbal communication in noisy environments can be hard. Speech enhancement using head-worn microphone arrays, such as hearing aids or augmented reality devices offers the opportunity to make it easier. However, the highly dynamic nature of the listening situation presents some challenges.

Radial sampling pattern is an important signal acquisition strategy in magnetic resonance imaging (MRI) owing to better immunity to motion-induced artifacts and less pronounced aliasing due to undersampling compared to the Cartesian sampling. 

Decentralized stochastic gradient descent (SGD) is a driving engine for decentralized federated learning (DFL). The performance of decentralized SGD is jointly influenced by inter-node communications and local updates.

Human centric visual analysis tasks are essential to computer vision since humans are the key element for cameras to analyze. In this talk, I will mainly focus on 4 visual analysis tasks on human hand, gesture, pose, and action respectively.

Graph neural networks (GNNs) have achieved impressive results in various graph learning tasks and they have found their way into many application domains. Despite their proliferation, our understanding of their robustness properties is still very limited. 

Deep learning-based methods have achieved remarkable success in image restoration and enhancement, but are they still competitive when there is a lack of paired training data? As one such example, this work explores the low-light image enhancement problem, where in practice it is extremely challenging to simultaneously take a low-light and a normal-light photo of the same visual scene. 

Recent advances in multimodal processing have led to promising solutions for speech-processing tasks. One example is automatic speech recognition (ASR), which is a key component in current speech-based systems.