Publications associées à Dépouillement

Discrete-Choice Mining of Social Processes

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

EPFL2021

Detecting animals in African Savanna with UAVs and the crowds

Stéphane Joost, Devis Tuia

Unmanned aerial vehicles (UAVs) offer new opportunities for wildlife monitoring, with several advantages over traditional field-based methods. They have readily been used to count birds, marine mammals and large herbivores in different environments, tasks ...

Elsevier2017

Online Collaborative Prediction of Regional Vote Results

Patrick Thiran, Matthias Grossglauser, Mohammad Emtiyaz Khan, Vincent Etter

We consider online predictions of vote results, where regions across a country vote on an issue under discussion. Such online predictions before and during the day of the vote are useful to media agencies, polling institutes, and political parties, e.g., t ...

IEEE2016

Combine and Conquer : Mining Social Systems for Prediction

Vincent Etter

In this thesis, we explore the application of data mining and machine learning techniques to several practical problems. These problems have roots in various fields such as social science, economics, and political science. We show that computer science tec ...

EPFL2015

Mining Democracy

Patrick Thiran, Matthias Grossglauser, Julien Pierre Sacha Herzen, Vincent Etter

Switzerland has a long tradition of direct democracy, which makes it an ideal laboratory for research on real-world politics. Similar to recent open government initiatives launched worldwide, the Swiss government regularly releases datasets related to stat ...

2014

Fusion of Multi-Atlas Segmentations with Spatial Distribution Modeling

Jean-Philippe Thiran, Meritxell Bach Cuadra, Subrahmanyam Venkata Ravi Mohana Sai Gorthi

In recent years, multi-atlas fusion methods have gained significant attention in medical image segmentation. In this paper, we propose a general Markov Random Field (MRF) based framework that can perform edge-preserving smoothing of the labels at the time ...

2011

Video Text Recognition using Sequential Monte Carlo and Error Voting Methods

Jean-Marc Odobez, Datong Chen

This paper addresses the issue of segmentation and recognition of text embedded in video sequences from their associated text image sequence extracted by a text detection module. To this end, we propose a probabilistic algorithm based on Bayesian adaptive ...

2005