Thesis (Master) algorithm development for in-field sharpness measurement using traffic signs

Fraunhofer-Gesellschaft; Ingolstadt; Vor Ort; EUR 30.000 - 50.000; Vollzeit

Zusammenfassung

An established industry player is seeking motivated students for a master’s thesis in machine learning and computer vision. This exciting opportunity involves developing an algorithm to assess image sharpness from automotive cameras, particularly focusing on traffic signs. As reliance on car cameras grows for applications like autonomous driving, ensuring optimal clarity is crucial. You will work in a supportive environment with professional supervision on versatile projects, gaining hands-on experience in a modern research infrastructure. If you are passionate about technology and eager to contribute to innovative research, this role is perfect for you.

Leistungen

Flexible working hours

Professional supervision

Open-minded working atmosphere

Modern research infrastructure

Qualifikationen

• Enrolled in a relevant field of study such as Data Science or Computer Science.
• Strong background in machine learning and computer vision is essential.

Aufgaben

• Develop an algorithm to evaluate the sharpness of images from automotive cameras.
• Focus on ensuring optimal image clarity for traffic signs.

Kenntnisse

Machine Learning

Deep Learning

Computer Vision

Python

C++

Teamwork

Creativity

Ausbildung

Data Science

Electrical and Information Engineering

Physics

Aeronautical and Automotive Engineering

Computer Science

Mathematics

Mechanical Engineering

Jobbeschreibung

At the Fraunhofer Application Center »Connected Mobility and Infrastructure«, we investigate and
develop concepts to design the mobility of the future in a safer, more efficient and resource-saving way.
We are dedicated to current research questions on automated and cooperative driving and combine a wide
range of competencies in the fields of sensor technology, communication and artificial intelligence. In the
process, we use synergies with local industry and work closely with the city of Ingolstadt and its partners.

What you will do

For our current research projects, we are looking for motivated students who would like to write their
final thesis in the field of machine learning / computer vision. The primary goal of this master’s thesis is to
develop an algorithm that can accurately and efficiently evaluate the sharpness of images captured by
automotive cameras, with focus on traffic signs. Given the increasing reliance on car cameras for
applications ranging from autonomous driving to traffic surveillance, ensuring optimal image clarity is
crucial. Traffic signs, with their standardized design and critical importance for navigation, are ideal
reference points for this process.

What you bring to the table

– enrolled in one of the following or related fields of study: Data Science, Electrical and Information
Engineering, Physics, Aeronautical and Automotive Engineering, Computer Science, Mathematics or
Mechanical Engineering
– strong background in machine learning, deep learning and / or computer vision
– good programming skills in Python (and C++)
– basic knowledge of optics including concepts like PSF, MTF, sharpness, aberrations etc.
– motivation and ability to work in a team
– initiative and creativity
– very good grades

What you can expect

– versatile and practical projects
– professional supervision
– motivated teams in an open-minded working atmosphere
– a modern research infrastructure and
– flexible working hours

Interested? Apply online now. We look forward to getting to know you!

If you have any questions, please contact us stating the reference number IVI-Hiwi-00714.

Contact

Prof. Dr. Gordon Elger
[e-mail]
Telefon [phone]

Fraunhofer Application Center »Connected Mobility and Infrastructure«
Visiting address
Stauffenbergstrasse 2a
85051 Ingolstadt
Postal address
Technische Hochschule Ingolstadt
Esplanade 10
85049 Ingolstadt
Fraunhofer Institute for Transportation and Infrastructure Systems IVI
www.ivi.fraunhofer.de
Requisition Number: IVI-Hiwi-00714 Application Deadline: