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Publications associées (8)

Learning-based techniques for lensless reconstruction

In this internship, I explore different optimization algorithms for lensless imaging. Lensless imaging is a new imaging technique that replaces the lens of a camera with a diffuser mask. This allows for simpler and cheaper camera hardware. However, the rec ...

2023

Burst Vision Using Single-Photon Cameras

Edoardo Charbon, Paul Mos, Mohit Gupta

Single-photon avalanche diodes (SPADs) are novel image sensors that record the arrival of individual photons at extremely high temporal resolution. In the past, they were only available as single pixels or small-format arrays, for various active imaging ap ...

IEEE COMPUTER SOC2023

Spiking Neural Networks Trained With Backpropagation For Low Power Neuromorphic Implementation Of Voice Activity Detection

Milos Cernak, Giorgia Dellaferrera

Recent advances in Voice Activity Detection (VAD) are driven by artificial and Recurrent Neural Networks (RNNs), however, using a VAD system in battery-operated devices requires further power efficiency. This can be achieved by neuromorphic hardware, which ...

IEEE2020

Learning Neural Connectivity from Firing Activity: Scalable Algorithms with Provable Guarantees

Martin Vetterli, Amin Karbasi, Amir Hesam Salavati

The connectivity of a neuronal network has a major effect on its functionality and role. It is generally believed that the complex network structure of the brain provides a physiological basis for information processing. Therefore, identifying the network’ ...

Springer New York LLC2018

Privacy in Recommender Systems

Mahsa Taziki

The upsurge in the number of web users over the last two decades has resulted in a significant growth of online information. Recommenders are machine learning approach and are becoming one of the main ways to navigate the Internet. They recommend appropria ...

EPFL2018

Semi-Supervised Segmentation of Ultrasound Images Based on Patch Representation and Continuous Min Cut

Jean-Philippe Thiran, Meritxell Bach Cuadra, Xavier Bresson, Olivier Cuisenaire, Nawal Houhou, Anca-Ramona Ciurte

Ultrasound segmentation is a challenging problem due to the inherent speckle and some artifacts like shadows, attenuation and signal dropout. Existing methods need to include strong priors like shape priors or analytical intensity models to succeed in the ...

Public Library Science2014

Coordination and Sampling in Distributed Constraint Optimization

Brammert Ottens

The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...

EPFL2012

Branch-and-Prune Search Strategies for Numerical Constraint Solving

Boi Faltings, Marius-Calin Silaghi, Xuan-Ha Vu

When solving numerical constraints such as nonlinear equations and inequalities, solvers often exploit pruning techniques, which remove redundant value combinations from the domains of variables, at pruning steps. To find the complete solution set, most of ...

2005

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