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Predicting the long-term collective behaviour of fish pairs with deep learning

Publications associées (74)

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A deep learning approach to Cadastral Computing

Frédéric Kaplan, Isabella Di Lenardo, Sofia Ares Oliveira, Bastien Solal Emile Tourenc

This article presents a fully automatic pipeline to transform the Napoleonic Cadastres into an information system. The cadastres established during the first years of the 19th century cover a large part of Europe. For many cities they give one of the first ...

2019

Unsupervised Learning of Phase-Change-Based Neuromorphic Systems

Stanislaw Andrzej Wozniak

Neuromorphic systems provide brain-inspired methods of computing. In a neuromorphic architecture, inputs are processed by a network of neurons receiving operands through synaptic interconnections, tuned in the process of learning. Neurons act simultaneousl ...

EPFL2017

Machine Vision algorithms on cadaster plans

Sofia Ares Oliveira

Cadaster plans are cornerstones for reconstructing dense representations of the history of the city. However, as some of these handwritten documents are more than 200 years old, the establishment of processing pipeline for interpreting them remains extreme ...

2017

Deep(ly) Learning the Depth

Xun Victor Suo

We report on the use of deep learning algorithms to perform depth recovery in multiview imaging. We show that if enough training data are provided, a neural network such as multilayer perceptron can be trained to recover the depth in multiview imaging as a ...

2016

Design Methods for Miniature Underwater Soft Robots

Francesco Mondada, Daniel Burnier, Norbert Crot, Frank Bonnet

A robotic fish accepted by animals as conspecifics is a very powerful tool in behavioral biology. To obtain the acceptance of the device towards the animals, it should generate some visual stimuli that can be perceived by a living fish as attractive signal ...

Ieee2016

Mechanosensory interactions drive collective behaviour in Drosophila

Dario Floreano, Pavan P Ramdya, Pawel Lichocki, Lukas Frisch, Winnie Wing Yee Tse

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can ...

2015

A Deeper Look at Dataset Bias

Barbara Caputo, Tatiana Tommasi, Novi Patricia

The presence of a bias in each image data collection has recently attracted a lot of attention in the computer vision community showing the limits in generalization of any learning method trained on a specific dataset. At the same time, with the rapid deve ...

Springer Int Publishing Ag2015

The impact of privacy protection filters on gender recognition

Touradj Ebrahimi

Deep learning-based algorithms have become increasingly efficient in recognition and detection tasks, especially when they are trained on large-scale datasets. Such recent success has led to a speculation that deep learning methods are comparable to or eve ...

2015

Learning non-parametric basis independent models from point queries via low-rank methods

Volkan Cevher, Hemant Tyagi

We consider the problem of learning multi-ridge functions of the form f (x) = g(Ax) from point evaluations of f. We assume that the function f is defined on an l(2)-ball in R-d, g is twice continuously differentiable almost everywhere, and A is an element ...

Elsevier2014

Models of Reward-Modulated Spike-Timing-Dependent Plasticity

Nicolas Frémaux

How do animals learn to repeat behaviors that lead to the obtention of food or other “rewarding” objects? As a biologically plausible paradigm for learning in spiking neural networks, spike-timing dependent plasticity (STDP) has been shown to perform well ...

EPFL2013