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Master Thesis - Synthetic Heat: Generating synthetic datasets of thermal images using Generative Adverserial Network (GAN) methods i Lund

Axis enables a smarter and safer world by creating network solutions that provide insights for improving security and new ways of doing business. As the industry leader in network video, Axis offers products and services for video surveillance and analytics, access control, and audio systems. Axis has more than 3,000 dedicated employees in over 50 countries and collaborates with partners worldwide to deliver customer solutions.

Om tjänsten

Category: Machine Learning, Imaging, Thermal, GAN

Scope: 2 students completing 30 credits (20 weeks) each.

Background
The aim of this masters project is to explore the possibility to create synthetic datasets of thermal images which can then be used in various applications as training data for other object detection, machine vision and deep learning models.

The purpose of this masters thesis is to:

  • Using GANs (or similar techniques) to produce synthetic thermal datasets.
  • Test in a simple model how well this data works as a substitute for real data.
  • Exploring possibilities with augmented data and knowledge based training.
  • Investigate ratio of synthetic data to real data for training quality.

Absolute requirements
Programing skills in one or more of the following: Python and/or C/C++

Appreciated requirements
Knowledge of Tensorflow and Keras

OK, I am interested! What do I do now?
You are valuable to us – how nice that you are interested in one of our proposals! There are a few things for you to keep in mind when applying.

  • Applications are accepted in both Swedish and English, and you apply via the proposal advert.
  • The announced theses are open only to students affiliated with a Swedish university/college either directly or via an exchange program.
  • When the thesis proposal states that it includes two students working together, we would like you to apply in pairs. In these cases, send one application each but make sure to clearly state in your application who your co-applicant is. If you have any questions regarding this, please do not hesitate to contact us.
  • Please attach your CV and University/college grade summary.

Contact Information
For information or questions regarding technical issues, please contact:   

For general or practical questions, please contact our Master Thesis Coordinator:

Publicerad den

28-09-2020

Extra information

Status
Stängd
Ort
Lund
Typ av kontrakt
Examensarbete
Typ av jobb
IT
Körkort önskas
Nej
Tillgång till bil önskas
Nej
Personligt brev krävs
Nej

Lund | IT | Examensarbete

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