Course paper / final thesis, Student placement, Internship

Person Tracking in Aerial Image Sequences using Deep Learning Techniques

Starting date


Duration of contract

Internship: as specified in the study regulations / Master thesis: 6 months

Type of employment


"Cutting-edge research requires excellent minds – particularly more females – at all levels. Launch your mission with us and send in your application now!" Prof. Pascale Ehrenfreund - Chair of the DLR Executive Board

Development of a computer vision algorithm based on deep learning approaches (e.g., Convolutional Neural Networks - CNNs) to track people in aerial image sequences. Reviewing the existing methods and benchmark them on DLR’s own person tracking dataset.

Your qualifications:

  • Bachelor’s Degree in Computer Science, Mathematics, Geosciences and comparable studies
  • scientific background Computer Vision, Signal Processing, Remote Sensing or a related discipline
  • programming skills are required (preferred is Python)
  • experience with Machine Learning and Deep Learning frameworks, such as Pytorch or Tensorflow
  • English fluent

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Technical contact

Maximilian Langheinrich
Phone: +49 8153 283-130

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Vacancy 38376

HR department Oberpfaffenhofen

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DLR site Oberpfaffenhofen

To location

DLR Remote Sensing Technology Institute

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