Thesis: Incremental Learning for Autonomous Driving Systems

4 weeks ago


Gothenburg, Västra Götaland, Sweden Semcon Full time
Job Title: Thesis: Incremental Learning with Open World Object Detection

At Semcon, we are seeking a highly skilled researcher to explore the feasibility and efficiency of implementing open world object detection in autonomous driving systems. The successful candidate will focus on the ability of open world object detection to handle edge cases and integrate incremental training mechanisms.

Key Responsibilities:
  • Investigate the performance of traditional object detection models in autonomous driving compared to open world object detection models when encountering edge cases.
  • Develop strategies to ensure the robustness and reliability of an open world object detection system when faced with novel objects, such as unseen animals or unexpected obstacles.
  • Optimize the computational and storage overhead introduced by incremental learning in open world object detection for real-time processing in an autonomous vehicle.
Requirements:

The ideal candidate will have a strong background in computer vision, machine learning, and autonomous driving systems. Experience with open world object detection and incremental learning is highly desirable.

We offer a dynamic and collaborative work environment, with opportunities for professional growth and development. If you are passionate about autonomous driving and open world object detection, we encourage you to apply.



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