Publications related to Multimodal Signal Processing: Methods and Techniques to Build Multimodal Interactive Systems

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From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Michaël Unser, Dimitri Nestor Alice Van De Ville, Michael Stefan Daniel Liebling

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Lippmann Photography: A Signal Processing Perspective

Martin Vetterli, Arnaud Latty, Adam James Scholefield, Gilles Baechler, Michalina Wanda Pacholska

Lippmann (or interferential) photography is the first and only analog photography method that can capture the full color spectrum of a scene in a single take. This technique, invented more than a hundred years ago, records the colors by creating interferen ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Large evanescently-induced Brillouin scattering at the surrounding of a nanofibre

Luc Thévenaz, Li Zhang, Flavien Gyger

Brillouin scattering has been widely exploited for advanced photonics functionalities such as microwave photonics, signal processing, sensing, lasing, and more recently in micro- and nano-photonic waveguides. Most of the works have focused on the opto-acou ...

2022

Characterization of Real-World Power System Signals in Non-Stationary Conditions using a Dictionary Approach

Mario Paolone, Asja Derviskadic, Guglielmo Frigo, Alexandra Cameron Karpilow

As power grids transition towards low-inertia net-works based on converter-interfaced renewable energy resources, they become increasingly vulnerable to extreme dynamics. Currently, the most advanced methods for signal processing in power systems are embed ...

IEEE2021

DiffuserCam Project

William Cappelletti, Jonathan Philippe Reymond, Matteo Pariset

We test the reconstruction power of a lensless cam- era on a custom dataset. We define a linear inverse problem on the raw image, based on a PSF estimation of the the sensing device and the actual captures. We implement various regularizations to enforce s ...

2021

Graph Signal Processing for Machine Learning: A Review and New Perspectives

Pascal Frossard, Michael Bronstein, Laura Toni, Xiaowen Dong

The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning. Graph signal processing ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics

José Luis Abelleira Fernández, Sofia Moco

aSummary: Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches re ...

OXFORD UNIV PRESS2020