144 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR14 papers
- Centre National de la Recherche ScientifiqueFR11 papers
- Université de LilleFR11 papers
- IMT Nord EuropeFR10 papers
- Institut Mines-TélécomFR5 papers
- École Centrale de LilleFR3 papers
- Universitat de ValènciaES3 papers
- University College LondonGB3 papers
- Universidad Carlos III de MadridES2 papers
- University of CambridgeGB2 papers
- University of FlorenceIT2 papers
- University of SheffieldGB2 papers
15 papers
Joint Modeling of Received Power, Mean Delay, and Delay Spread for Wideband Radio Channels
Ayush Bharti, Ramoni Adeogun, Xuesong Cai +4
We propose a multivariate log-normal distribution to jointly model received power, mean delay, and root mean square (rms) delay spread of wideband radio channels, referred to as th…
Improving STDP-based Visual Feature Learning with Whitening
Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco
In recent years, spiking neural networks (SNNs) emerge as an alternative to deep neural networks (DNNs). SNNs present a higher computational efficiency using low-power neuromorphic…
Dynamic Facial Expression Generation on Hilbert Hypersphere with Conditional Wasserstein Generative Adversarial Nets
Naima Otberdout, Mohamed Daoudi, Anis Kacem +2
In this work, we propose a novel approach for generating videos of the six basic facial expressions given a neutral face image. We propose to exploit the face geometry by modeling…
Impact of facial landmark localization on facial expression recognition
Romain Belmonte, Benjamin Allaert, Pierre Tirilly +3
Although facial landmark localization (FLL) approaches are becoming increasingly accurate for characterizing facial regions, one question remains unanswered: what is the impact of…
Unsupervised Visual Feature Learning with Spike-timing-dependent Plasticity: How Far are we from Traditional Feature Learning Approaches?
Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco +2
Spiking neural networks (SNNs) equipped with latency coding and spike-timing dependent plasticity rules offer an alternative to solve the data and energy bottlenecks of standard co…
Deep Covariance Descriptors for Facial Expression Recognition
Naima Otberdout, Anis Kacem, Mohamed Daoudi +2
In this paper, covariance matrices are exploited to encode the deep convolutional neural networks (DCNN) features for facial expression recognition. The space geometry of the covar…
Spatial Field Reconstruction and Sensor Selection in Heterogeneous Sensor Networks with Stochastic Energy Harvesting
Pengfei Zhang, Ido Nevat, Gareth W. Peters +2
We address the two fundamental problems of spatial field reconstruction and sensor selection in het- erogeneous sensor networks. We consider the case where two types of sensors are…
Metropolis Sampling
Luca Martino, Victor Elvira
Monte Carlo (MC) sampling methods are widely applied in Bayesian inference, system simulation and optimization problems. The Markov Chain Monte Carlo (MCMC) algorithms are a well-k…
The Recycling Gibbs Sampler for Efficient Learning
Luca Martino, Victor Elvira, Gustau Camps-Valls
Monte Carlo methods are essential tools for Bayesian inference. Gibbs sampling is a well-known Markov chain Monte Carlo (MCMC) algorithm, extensively used in signal processing, mac…
Independent Resampling Sequential Monte Carlo Algorithms
Roland Lamberti, Yohan Petetin, François Desbouvries +1
Sequential Monte Carlo algorithms, or Particle Filters, are Bayesian filtering algorithms which propagate in time a discrete and random approximation of the a posteriori distributi…
Generalized Multiple Importance Sampling
Víctor Elvira, Luca Martino, David Luengo +1
Importance Sampling methods are broadly used to approximate posterior distributions or some of their moments. In its standard approach, samples are drawn from a single proposal dis…
A Bayesian Compressed Sensing Kalman Filter for Direction of Arrival Estimation
Matthew Hawes, Lyudmila Mihaylova, Francois Septier +1
In this paper, we look to address the problem of estimating the dynamic direction of arrival (DOA) of a narrowband signal impinging on a sensor array from the far field. The initia…
How Can Subsampling Reduce Complexity in Sequential MCMC Methods and Deal with Big Data in Target Tracking?
Allan De Freitas, François Septier, Lyudmila Mihaylova +1
Target tracking faces the challenge in coping with large volumes of data which requires efficient methods for real time applications. The complexity considered in this paper is whe…
Gauge Invariant Framework for Shape Analysis of Surfaces
Alice Barbara Tumpach, Hassen Drira, Mohamed Daoudi +1
This paper describes a novel framework for computing geodesic paths in shape spaces of spherical surfaces under an elastic Riemannian metric. The novelty lies in defining this Riem…
Langevin and Hamiltonian based Sequential MCMC for Efficient Bayesian Filtering in High-dimensional Spaces
Francois Septier, Gareth W. Peters
Nonlinear non-Gaussian state-space models arise in numerous applications in statistics and signal processing. In this context, one of the most successful and popular approximation…