ENS - Ecole Normale Supérieure
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Publications

M1 or M2
Internship
Information
LSP
Laboratory:

Laboratoire des Systèmes Perceptifs

Address

29 rue d'Ulm

75005 Paris France

 

Team
Vision
Adviser
Length of internship
Minimum 3 months
Language
English

Visual processing of simple image elements (such as lines and edges) does not happen inside a cognitive vacuum: it may differ when those simple elements are embedded within natural scenes that look more like what we see every day, as opposed to th e featureless backgrounds that are normally used in the laboratory. We know a good amount about the mechanisms that support vision under the latter conditions (i.e. involving a simple stimulus with no natural meaningful content), but we know virtually nothing about how those mechanisms may change and/or be augmented/replaced by new mechanisms under conditions that are closer to natural vision (i.e. when the image starts making sense and contains recognizable objects). Your project would attempt to understand this transition from elementary vision to natural vision. Below is an example of a relevant publication that looked at this question: Neri, P. (2014). Semantic control of feature extraction from natural scenes. Journal of Neuroscience, 34, 2374-2388. Prior experience with computer programming (C++, Matlab, Python) is highly desirable.
 

M1 ou M2
Stage
Information
LSP
Laboratory:

Laboratoire des Systèmes Perceptifs

Address

29 rue d'Ulm

75005 Paris France

 

Team
Vision
Adviser
Length of internship
3 mois minimum
Language
Anglais

Visual processing of simple image elements (such as lines and edges) does not happen inside a cognitive vacuum: it may differ when those simple elements are embedded within natural scenes that look more like what we see every day, as opposed to th e featureless backgrounds that are normally used in the laboratory. We know a good amount about the mechanisms that support vision under the latter conditions (i.e. involving a simple stimulus with no natural meaningful content), but we know virtually nothing about how those mechanisms may change and/or be augmented/replaced by new mechanisms under conditions that are closer to natural vision (i.e. when the image starts making sense and contains recognizable objects). Your project would attempt to understand this transition from elementary vision to natural vision. Below is an example of a relevant publication that looked at this question: Neri, P. (2014). Semantic control of feature extraction from natural scenes. Journal of Neuroscience, 34, 2374-2388. Prior experience with computer programming (C++, Matlab, Python) is highly desirable.