Job: Master thesis: False-Positive Suppression for Deep Learning based Object Detection in the Industry (m/w/d)


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Master thesis: False-Positive Suppression for Deep Learning based Object Detection in the Industry (m/w/d)

Über uns

SCHUNK is the world's first choice when it comes to equipping robots and production machines. No matter if it's smartphones or aircraft, compact cars or SUVs, knee joints or nasal sprays: SCHUNK's high-tech components are consistently at the forefront of production. More than 3,500 employees in 9 production facilities and 34 national subsidiaries ensure that precision, efficiency and reliability can be produced anywhere in the world. Digitalization and Industry 4.0 are an everyday reality for us, as our production transforms into a smart factory. Our customers include the who's-who of mechanical and plant engineering, robotics, automation and assembly handling, the automotive industry and its suppliers as well as the electronics industry. All of these industries rely on the topnotch gripping systems, clamping technology and depaneling machines from SCHUNK.
One of the problems that often arise when applying deep learning in the industry is the high number of false-positive cases. However, industrial applications often demand low false-positive rates to satisfy certain robustness criteria.

You are currently enrolled and looking for a company for your upcoming master thesis? We are offering the opportunity to apply your theoretical knowledge in practice in the Digital Products & Services department as soon as possible.

Ihre Aufgaben

Your Task:
  • Research of the state of the art and concept phase
  • Implementation and deployment of the methodology
  • Validation and test phase on real production system

Ihr Profil

Your profile:
  • Studies in the field of Science, Technology, Engineering or comparable
  • Programming background in python
  • Experience with computer vision and machine learning frameworks
  • Structured and independent approach to work
  • Team spirit