Skip to Main content Skip to Navigation
Theses

Modélisation bayésienne algorithmique de la reconnaissance visuelle de mots et de l'attention visuelle

Abstract : In this thesis, we propose an original theoretical framework of visual word recognition, and implement it mathematically to evaluate its ability to reproduce experimental observations of the field. A critical review of previous computational models leads us to define specifications in the form of a set of five hypotheses, that form the basis of the proposed theoretical framework: the model is built on a three-layer architecture (sensory, perceptual, lexical); letter processing is parallel; positional coding is distributed; finally, sensory processing involves gaze position, visual acuity, and visual attention distribution. To implement the model, we rely on the Bayesian algorithmic modeling methodology, and define the BRAID model (for "Bayesian word Recognition with Attention, Interference and Dynamics").
Document type :
Theses
Complete list of metadatas

Cited literature [205 references]  Display  Hide  Download

https://tel.archives-ouvertes.fr/tel-02368168
Contributor : Abes Star :  Contact
Submitted on : Monday, November 18, 2019 - 1:48:26 PM
Last modification on : Wednesday, August 26, 2020 - 3:00:26 AM

File

PHNIX_2018_diffusion.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-02368168, version 1

Collections

Citation

Thierry Phenix. Modélisation bayésienne algorithmique de la reconnaissance visuelle de mots et de l'attention visuelle. Psychologie. Université Grenoble Alpes, 2018. Français. ⟨NNT : 2018GREAV075⟩. ⟨tel-02368168⟩

Share

Metrics

Record views

567

Files downloads

126