facebook tracking

Master Thesis - Camera-Radar fusion using deep learning


Autonomous driving systems and advanced driver assistance systems require a description of their surrounding environment. Part of this description is facilitated by fusing object information from different sensors. Historically, object fusion algorithms relied on classical methods. With emergence of advanced machine learning algorithms, new methods have been developed in recent years that enable sensor fusion to be carried out by deep neural networks.
Camera and Radar are two sensor modalities commonly used in many autonomous drive applications. These two sensors complement each other since they have different failure modes. Using deep neural networks to detect objects in camera images is a relatively well explored problem. In comparison, fusing radar and camera using a deep learning based technique is a recent emergent and less explored problem. The purpose of this thesis is to explore different network architectures that facilitate radar-camera fusion.

Project Description

In this master thesis project, you will focus on:

  • Perform a literature study on different existing network architectures for fusing camera and radar.
  • Implement, train and evaluate a deep neural net that fuses radar and camera.
  • Document the results and lessons learned.


We are looking for 2 students with an interest in deep learning for autonomous driving. The following skills would be highly valuable:

  • Python programming
  • Machine learning
  • Reading scientific papers
  • Handling large datasets

Having had deep learning related courses and some hands-on experience with these methods is a plus.

    Further information

    Please send in individual applications with CV, motivational letter and grade transcripts.

    Planned start: January 2022, with some flexibility.

    Final application date: 30th of November 2021

    Duration: 30 ECTS

    For questions regarding the project, please contact: maryam.fatemi@zenseact.com, mahandokht.rafidashti@zenseact.com

    Additional information

    • Remote status

      Flexible remote

    Or, know someone who would be a perfect fit? Let them know!

    Gothenburg, Sweden

    Lindholmspiren 2
    417 56 Göteborg Directions View page

    Making safe and intelligent mobility real.

    At Zenseact, we lead the global movement of crafting tomorrow's mobility with the software platform of choice. Our mission is to “Make safe and intelligent mobility real, for everyone, everywhere”. This statement marks our conviction and dedication to bring autonomous driving out on the streets for real and is at the center of everything we do.

    We could not dream of achieving this without our great teams of very talented people. We are on this journey together and our agile way of working is reflected throughout our entire organization; it is part of our culture and how we work, develop and grow together.


    Applicant tracking system by Teamtailor