[visionlist] Announce for a PhD student

Robin Baures robin.baures at cnrs.fr
Tue Jun 12 04:59:55 -05 2018

Dear Moderator of the vision list,

Could you please post that announce below?


*Beating Roger Federer: **
**Modeling visual learning and expertise through a bioinspired neural 
network embedded in an electronic device*

*Goal: *PhD grant.

*When: *starting from September 2018 (date may be flexible to some extent)

*Topic: *How do expert tennis players, like Roger Federer for example, 
predict if a ball will bounce in or out the field to decide if it should 
be played or not? After thousands of trajectory presentations, best 
champions have developed extraordinary skills in such a task, but little 
is known on how the visual system turns selective to spatiotemporal 
properties of the visual stimulus (e.g., 3D position, velocity and 
acceleration) and learns how to make an efficient use of it.
The goal of the project is to build an embedded system – based on FPGA 
circuits and ARM processor – an artificial neural network which would 
replicate – and perhaps beat – the visual and anticipatory performances 
of these expert players.
To achieve this goal successfully, we will develop a bio-inspired neural 
network, based on some of the key properties of human vision: the Smart 
NeuroCam (GST company) will be used to reproduce the retina functioning. 
It triggers its message under the form of spikes, in an asynchronous way 
(without any concept of frame per second), responding to spatial or 
temporal changes in the pattern of illumination. Several kinds of 
pre-processing filters can be implemented in VHDL language directly in 
the FPGA circuits, and the output is then sent to a neural network. The 
artificial network will learn to use this message, applying a simple 
learning rule, the Spike-Timing-Dependent Plasticity (STDP). This rule 
allows each neuron to become selective to a particular property of the 
stimulus, completely autonomously and with no supervision. Several 
layers will be built to allow perceiving more and more complex 
properties of the visual scene. Once the network will be established, 
its performances will be assessed in different conditions of learning 
and compared to those of the best tennis players.

The project is funded by a French National Research Agency (ANR), 
involving two sites and several researchers:
Robin Baurès, Benoit Cottereau, Timothée Masquelier and Simon Thorpe, 
CerCo, Toulouse.
Michel Paindavoine, GST, Dijon.

*Where: *The candidate will be based at CerCo, Toulouse (France), and 
will make the interface with the two sites, with regular trips. The 
computational neuroscience part will be done at Toulouse, and electronic 
part at Dijon.

Matlab (or Python) based simulations of numerical filters. These filters 
will be applied to the image processing from which spikes are generated 
and then sent to feed the neural network and STDP learning mechanism.
VHDL coding to implement these numerical filters into the FPGA circuits 
of the cameras
C/C++ coding of the neural network and STDP mechanism that should work 
on an embedded ARM processor system
Experimental tests that will allow evaluating the performance of the 
whole system, from spikes generation to visual properties learning of 
the embedded system, to predict tennis ball’s trajectories

*Required skills: *
Strong knowledge on electronic, and openness to computational neurosciences
Knowledge in signal-image processing, and artificial neural network
Interest for multidisciplinary research
Ability to turn smoothly autonomous, once the road has been set
Ability to be at the interface of two scientific fields and two working 
Programming with Matlab and/or Python for simulating the neural network
Programming in VHDL language for FPGA circuits
Programming in C/C++ language for porting the algorithms on ARM 
French is not a requirement if fluent in English, but willingness to 
learn would be beneficial

*C**itizenship Eligibility: *For security / defense reasons, an 
evaluation will be made of the candidates before any possible acceptation.

*Relevant publications for the project:*
Masquelier, T., Guyonneau, R. & Thorpe S.J. (2009). Competitive 
STDP-Based Spike Pattern Learning. Neural Comput, 21(5),1259-1276.
Masquelier, T. & Thorpe, S.J. (2007). Unsupervised learning of visual 
features through spike timing dependent plasticity. PLoS Comput Biol, 
Cottereau, B.R., McKee, S.P. & Norcia, A.M. (2014). Dynamics and 
cortical distribution of neural responses to 2D and 3D motion in human. 
Journal of Neurophysiology 111(3), 533-543.
SmartNeuroCam de GST : https://gsensing.eu/fr/category/sections/products

Robin Baurès, PhD
Associate Professor
CerCo, Université Toulouse 3, CNRS
CHU Purpan, Pavillon Baudot
31059 Toulouse Cedex 9 – France
Office phone: 0033 (0)5 62 74 62 15
Email : robin.baures at cnrs.fr

Pr Michel Paindavoine
GlobalSensing Technologies
14, rue Pierre de Coubertin
21000 Dijon
email : michel.paindavoine at gsensing.eu


Robin Baurès, PhD
Maitre de Conférences | Associate Professor

CerCo, Université Toulouse 3, CNRS
CHU Purpan, Pavillon Baudot
31059 Toulouse Cedex 9 - France

Office phone: 0033 (0)5 62 74 62 15

Mail:robin.baures at univ-tlse3.fr  |robin.baures at cnrs.fr


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