Thesis Code: 19002
Thesis Type: Master Thesis for Telecommunication Engineering, Computer Engineering or related fields
Research Area: Multi-Layer Wireless Solutions
Requirements
- Excellent software programming skills
- Strong experience with Python/bash scripting and Linux environment
- Strong experience with C/C++ programming languages
- Basic knowledge of image processing
- Basic knowledge of machine learning
Motivation
Accurate and time-efficient image processing tools are essential for autonomous driving vehicles. A timely detection of other vehicles, road users and obstacles can ensure to the autonomous vehicle the capability to perform safe road manoeuvres. Several cutting-edge tools are now being proposed by several research actors and companies. In the autonomous driving context, it is necessary to find the best trade-off between accuracy and time performance given the resources-constrained environment. A thorough evaluation is needed as well as a customization of the tools for the autonomous driving context.
Objective
The aim of the thesis is to evaluate different image processing tools for finding the most suited for the automotive driving context. Customization of the selected tool is the final target of the thesis.
The first part of the thesis will be devoted to the analysis of cutting-edge image processing tools for selecting the most suitable one for the specific targeted scenario. The evaluation will be based on different performance criteria. In the second part of the thesis, the student will customize the selected image processing tool for enhancing its performance for the context of autonomous driving.
The student will have the possibility to work with real-data coming from the field in an informal cutting-edge research laboratory using the latest available technologies on these fields.
Contact: send a resume with attached the list of exams to daniele.brevi@linksfoundation.com specifying the thesis code and title.