Applied Deep Learning for Computer Vision

Applied Deep Learning for Computer Vision

Deep Learning for Computer Vision can be applied on different application-domains such as autonomous driving, anomaly detection, document layout recognition and many more. Throughout the recent years, these tasks have been solved with ever-evolving techniques adding to a vast box of tools to deep learning researchers and practitioners alike. 

The project is aimed towards building a fundamental understanding of current techniques for constructing learning based models, so that they can be applied to problems in the realm of 2D image segmentation, image retrieval and 3D point cloud analysis.

Associated research projects:


  • Successful completion of the course “Image Analysis and Object Recognition” 
  • Good programming skills in Python

Auxiliary Materials:

  • Datacamp Python/Shell ( free for course participants )
  • Udacity PyTorch Intro ( free course )
  • Deep Learning Specialisation ( free course  )
  • Deep Learning with PyTorch ( free ebook )