pôle SIS

SIGNAL
Biomed - Biomedical Signal Processing I3S researchers working on biomedical signals aim to develop strong local collaborations around the processing, analysis and modeling of signals issued from Medicine and Biology. Inheriting from the former BIOMED group at I3S, ongoing research partnerships include the Cardiology Departments of Nice University Hospital (CHU) and Monaco Princess Grace Hospital (CHPG), as well as Nice University Sports Department (STAPS) together with the Institute of Sport Medicine of Monaco (IM2S). [for more information, click here...]	SigNet - Signal Processing and Networks Signal Processing has been instrumental in the development of wireless networks, for example the introduction of MIMO (Multiple Input Multiple Output, i.e. multiple antennas at the transmitter and multiple antennas at the receiver) has significantly increased the capacity of wireless links and hence networks. Unfortunately, the huge capacity gains on the link level do not scale at the network level, ... [for more information, click here...]
Tensors - Tensors in signal processing The aim of this research project is two-fold. On one hand, theoretical problems related to tensors will be addressed: tensor decompositions, uniqueness and identifiability properties of tensor models, numerical algorithms for parameter estimation. On the other hand, Telecommunications, Environment, Radar Imaging or EEG Imaging will serve as leading applications. [for more information, click here...]
IMAGES
MediaCoding - Multimedia image coding and processing The researchers working on this research activity aim to develop theoretical tools relative to image coding, processing and learning. They draw their inspiration from the domains of image processing, information theory and multiresolution analysis (wavelets) to develop applications such as mesh coding, out-of-core 3D processing and rendering, bio-inspired image/video coding, and Machine Learning for image Classification. [for more information, click here...]	Morpheme - Analyzing and Processing Images for Biology The objectives of this research activity are to characterize and model the development and the morphological properties of biological structures from the cell to the supra-cellular scale. This work is at the interface between computational science and biology. It aims at understanding the morphological changes that occur during development combining in vivo imaging, image processing and computational modeling. [for more information, click here...]
SYSTEMS
ANM - Autonomous navigation and mapping Sensor networks and collective mobile robotics are two closely related fields where the ultimate goal is to be able to process a large amount of data simultaneously collected by distinct sensors in order to observe a given spatial field. Usually, the distinction between the two fields is determined by the different amounts of computing power, energy and communication capabilities that are assumed in each element of the set of participating nodes. [for more information, click here...]	Condor - Drones This research activity focuses on the development of the fundamental science and technology underlying the operation of dynamical aerial robotic vehicles. Due to its low cost, low energy use, and rich information content, vision is a unique sensor modality for control of robotic vehicles. We will develop control and image processing algorithms, based on rigorous systems theoretic foundations that provide practical and simple control for autonomous and semi-autonomous robotic vehicles in unstructured and cluttered environments. [for more information, click here...]
SIM - System identification and modelling Nonlinear system modeling and identification. Based on the techniques developed in research area "Tensor Data and SIgnal Processing", tensor tools are applied to a new family of nonlinear models, the so called Volterra-Parafac models and extended to the tensor-based modeling... [for more information, click here...] Information, Entropies, and Divergences This research activity is conducted in collaboration with Prof. Nikolai Leonenko from Cardiff University, UK, on the properties of entropy and divergence estimators based on nearest-neighbor distances. The approach we used in [23] is based on the computation of conditional moments of nearest-neighbor distances. However, the approach of Joe Yukich [39], based on the subadditivity ... [for more information, click here...]