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Thesis Project Form

Title (tentative): A neuromorphic neural network for robot vision

Thesis advisor(s): Sabatini Silvio P., Michael Spratling (King's College London) E-mail:
Address: Via All'Opera Pia, 13 - 16145 Genova (III piano) Phone: (+39) 010 33 52092
Description

Motivation and application domain
Developing biologically-inspired algorithms for visual perception to either model the biological visual system or to develop methods for computer vision or robot control.

General objectives and main activities
The thesis will concern, in general, bio-inspired computational algorithms for visual perception. In particular, the algorithms will be based on neural network models inspired by theories of cortical visual information processing. It will be particularly concerned with developing a system for analysing stereo visual information, with the aim of either stereo disparity estimation, or the control of eye/camera movements. The performance of the developed algorithm will be quanitatively assessed to validate the approach.

Training Objectives (technical/analytical tools, experimental methodologies)
To gain practical experience in developing and using neural network models, to gain MATLAB programming experience, experience applying benchmark assessment methods and of performing quantitative analysis of results, experience using a robot simulator (such as the iCub simulator).

Place(s) where the thesis work will be carried out: Department of Informatics, King's College London and DIBRIS, University of Genoa

Additional information

Pre-requisite abilities/skills: (MATLAB) programming skills

Maximum number of students: 1

Financial support/scholarship: ERASMUS+ placement