Modeling and Analysis of Distortion Caused by Markov-Model Burst Packet Losses in Video Transmission

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Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

Alberto Antonietti, Davide Bella, Pranav Rai, Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Michael Reimann, Marwan Muhammad Ahmed Abdellah, Werner Alfons Hilda Van Geit, Lida Kanari, Srikanth Ramaswamy, James Gonzalo King, Alexis Arnaudon, Ying Shi, András Ecker, Jean-Denis Georges Emile Courcol, Armando Romani, Pramod Shivaji Kumbhar, Judit Planas Carbonell, Michael Emiel Gevaert, Nadir Roman Guerrero, Liesbeth Maria L Vanherpe, Huanxiang Lu, Mohameth François Sy, Cristina Colangelo, Juan Bautista Hernando Vieites, Cyrille Pierre Henri Favreau, Genrich Ivaska, Anna-Kristin Kaufmann, Joni Henrikki Herttuainen, Elvis Boci, Vishal Sood, Thomas Brice Delemontex, Fabien Petitjean, Julian Martin Budd, Mustafa Kerem Kurban

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

2024

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Ieee Computer Soc2023

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

Michaël Unser, Pakshal Narendra Bohra, Pol del Aguila Pla

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

2023

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Touradj Ebrahimi, Michela Testolina, Davi Nachtigall Lazzarotto

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

2023

Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Michael Christoph Gastpar, Aditya Pradeep

One major challenge in distributed learning is to efficiently learn for each client when the data across clients is heterogeneous or non iid (not independent or identically distributed). This provides a significant challenge as the data of the other client ...

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Automated Human Motion Analysis and Synthesis

Sena Kiciroglu

Human motion analysis and synthesis is integral to many computer vision applications, from autonomous driving to sports analysis. In this thesis, we address several problems in this domain. First we consider active viewpoint selection for pose estimation w ...

EPFL2023

Data-driven modeling of beam loss in the LHC

Tatiana Pieloni, Michael Schenk, Ekaterina Krymova, Loïc Thomas Davies Coyle

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

FRONTIERS MEDIA SA2023

A Framework for Autonomic Computing for In Situ Imageomics

Nina Marion Aurélia Van Tiel

In situ imageomics is a new approach to study ecological, biological and evolutionary systems wherein large image and video data sets are captured in the wild and machine learning methods are used to infer biological traits of individual organisms, animal ...

The Institute of Electrical and Electronics Engineers, Inc2023

Towards a multiscale point cloud structural similarity metric

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...

IEEE2023

Unsupervised Visual Entity Abstraction towards 2D and 3D Compositional Models

Beril Besbinar

Object-centric learning has gained significant attention over the last years as it can serve as a powerful tool to analyze complex scenes as a composition of simpler entities. Well-established tasks in computer vision, such as object detection or instance ...

EPFL2022