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Pascal Frossard

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Related publications (427)

Page 4 of 22

Network coding: from theory to media streaming

Pascal Frossard, Nikolaos Thomos

Network coding has recently emerged as an alternative to traditional routing algorithms in communication systems. In network coding, the network nodes can combine the packets they receive before forwarding them to the neighbouring nodes. Intensive research ...

2009

Streaming of Scalable Video from Multiple Servers using Rateless Codes

Pascal Frossard, Jean-Paul Wagner

This paper presents a framework for efficiently streaming scalable video from multiple servers over heterogeneous network paths. We propose to use rateless codes, or Fountain codes, such that each server acts as an independent source, without the need to c ...

2006

Utility-based Packet Scheduling in P2P Mesh-based Multicast

Pascal Frossard

We consider streaming video content over an overlay network of peer nodes. We propose a novel streaming strategy that is built on utility-based packet scheduling and proportional resource sharing in order to fight against free- riders. Each of the peers em ...

2009

Reinforcement Learning-Based Opportunistic Routing for Live Video Streaming over Multi-Hop Wireless Networks

Pascal Frossard

Real-time video services are usually delay sensitive and have strict constraints on the transmission reliability, which poses challenges to live video streaming over multi-hop wireless networks, since the unpredictable packet losses and network congestions ...

2017

Anatomy-Informed Multimodal Learning for Myocardial Infarction Prediction

Pascal Frossard, Emmanuel Abbé, Ntorina Thanou, Ortal Yona Senouf, Ivan-Daniel Sievering

Goal: In patients with coronary artery disease, the prediction of future cardiac events such as myocardial infarction (MI) remains a major challenge. In this work, we propose a novel anatomy-informed multimodal deep learning framework to predict future MI ...

2024

Ultrasound Tomography with Learned Dictionaries

Pascal Frossard, Martin Vetterli, Ivana Tosic, Ivana Jovanovic

We propose a new method for imaging sound speed in breast tissue from measurements obtained by ultrasound tomography (UST) scan- ners. Given the measurements, our algorithm finds a sparse image representation in an overcomplete dictionary that is adapted t ...

2010

Wide-baseline object interpolation using shape prior regularization of epipolar plane images

Pascal Frossard, Thomas Maugey

This paper considers the synthesis of intermediate views of an object captured by two calibrated and widely spaced cameras. Based only on those two very different views, our paper proposes to reconstruct the object Epipolar Plane Image Volume [1] (EPIV), w ...

2017

Graph-Based Light Field Super-Resolution

Pascal Frossard, Mattia Rossi

Light field cameras can capture the 3D information in a scene with a single exposure. This special feature makes light field cameras very appealing for a variety of applications: from post capture refocus, to depth estimation and image-based rendering. How ...

2017

Quality-Constrained Encoding Optimization for Omnidirectional Video Streaming

Pascal Frossard, Roberto Gerson De Albuquerque Azevedo

Omnidirectional video streaming is usually implemented based on the representations of tiles, where the tiles are obtained by splitting the video frame into several rectangular areas and each tile is converted into multiple representations with different r ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Revealing Brain and Spinal Cord Functional Networks by Block-Structured Graph Laplacian Mixture Models

Pascal Frossard, Dimitri Nestor Alice Van De Ville, Ilaria Ricchi, Ekansh Sareen, William Cappelletti

The Graph Laplacian Mixture Model (GLMM) allows to infer multiple underlying graph structures from multivariate time series data. Given its effectiveness in identifying brain states from brain activity measured by functional magnetic resonance imaging (fMR ...

IEEE2025

Polynomial Filtering for Fast Convergence in Distributed Consensus

Pascal Frossard, Effrosyni Kokiopoulou

In the past few years, the problem of distributed consensus has received a lot of attention, particularly in the framework of ad hoc sensor networks. Most methods proposed in the literature address the consensus averaging problem by distributed linear iter ...

2009

Classification-Specific Feature Sampling for Face Recognition

Pascal Frossard, Effrosyni Kokiopoulou

Feature extraction based on different types of signal filters has received a lot of attention in the context of face recognition. It generally results into extremely high dimensional feature vectors, and sampling of the coefficients is required to reduce t ...

2006

PRIME: A Few Primitives Can Boost Robustness to Common Corruptions

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Apostolos Modas, Guillermo Ortiz Jimenez

Despite their impressive performance on image classification tasks, deep networks have a hard time generalizing to unforeseen corruptions of their data. To fix this vulnerability, prior works have built complex data augmentation strategies, combining multi ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Kernel Regression for Graph Signal Prediction in Presence of Sparse Noise

Pascal Frossard, Arun Venkitaraman

In presence of sparse noise we propose kernel regression for predicting output vectors which are smooth over a given graph. Sparse noise models the training outputs being corrupted either with missing samples or large perturbations. The presence of sparse ...

IEEE2019

Hierarchical Training of Deep Neural Networks Using Early Exiting

Pascal Frossard, Liza Carol Andrea Dunbar, Ahmet Caner Yüzügüler, Yamin Sepehri

Deep neural networks (DNNs) provide state-of-the-art accuracy for vision tasks, but they require significant resources for training. Thus, they are trained on cloud servers far from the edge devices that acquire the data. This issue increases communication ...

Ieee-Inst Electrical Electronics Engineers Inc2024

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Pascal Frossard

Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by joint ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Rate distortion analysis in a disparity compensated scheme

Pascal Frossard, Thomas Maugey

This paper addresses the problem of rate distortion analysis in the context of multi-view image coding, where images are predicted via disparity compensation based on depth map. We first present an an- alytical model for the variance of the residual error ...

2011

Online Network Source Optimization with Graph-Kernel MAB

Pascal Frossard

We propose Grab-UCB, a graph-kernelmulti-arms bandit algorithm to learn online the optimal source placement in large scale networks, such that the reward obtained from a priori unknown network processes is maximized. The uncertainty calls for online learni ...

Springer International Publishing Ag2023

Packet Selection and Scheduling for Multipath Video Streaming

Pascal Frossard, Dan Jurca

This paper addresses the problem of choosing the best streaming policy for distortion optimal multipath video delivery, under delay constraints. The streaming policy consists in a joint selection of the video packets to be transmitted, as well as their sen ...

2007

Adversarial training with informed data selection

Pascal Frossard, Javier Alejandro Maroto Morales

With the increasing amount of available data and advances in computing capabilities, deep neural networks (DNNs) have been successfully employed to solve challenging tasks in various areas, including healthcare, climate, and finance. Nevertheless, state-of ...

IEEE2022