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Algorithm Development for In-Field Sharpness Measurement using Traffic Signs

vor 1 Monat


Ingolstadt, Bayern, Deutschland Fraunhofer-Gesellschaft Vollzeit

At the Fraunhofer Application Center »Connected Mobility and Infrastructure«, we are seeking a motivated student to work on a master's thesis project focused on developing an algorithm for evaluating the sharpness of images captured by automotive cameras, with a focus on traffic signs. This project is part of our ongoing research in machine learning and computer vision, and the successful candidate will have the opportunity to contribute to the development of key technologies for the future of mobility.

Key Responsibilities:

  • Develop an algorithm for accurately and efficiently evaluating the sharpness of images captured by automotive cameras, with a focus on traffic signs.
  • Collaborate with our research team to integrate the developed algorithm into our existing research infrastructure.
  • Contribute to the development of new concepts and technologies for the future of mobility.

Requirements:

  • Enrolled in a relevant field of study, such as 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, and aberrations.
  • Motivation and ability to work in a team.
  • Initiative and creativity.
  • Very good grades.

What We Offer:

  • Flexible working hours.
  • Professional supervision.
  • Motivated teams in an open-minded working atmosphere.
  • A modern research infrastructure.

Fraunhofer is Europe's largest application-oriented research organization. Our research efforts are geared entirely to people's needs: health, security, communication, energy, and the environment. We are creative. We shape technology. We design products. We improve methods and techniques. We open up new vistas.