Starting this winter term, the chair for Multimedia Computing and Computer Vission is offering the follow-up master lecture Advanced Machine Learning and Computer Vision:

• Master CS or side-subject CS
• 2+2 lecture and tutorial
• Follow-up lecture to Mutlimedia II (INF-0092) / Machine Learning and Compter Vision (INF-0316)

This course is intended for graduate students in CS (or with side-subject CS) and builds on the foundations of our main master course Multimedia II / Machine Learning and Compter Vision. The lecture offers insights into the current development in machine learning, mainly at the border to computer vision. After an introduction to some fundamental techniques in machine learning and optimization (Support Vector Machines, Bipartite Graph Matching, Distance Transforms), it will cover the following topics with related concepts and techniques:

• Current deep learning architectures (ResNeXt, MobileNet, HRNet)
• Embedding Learning, (Visual) Word Embeddings
• Generative Adversarial Networks, Cycle GANs
• Attention mechanisms and Transformer networks
• Semantic and instance segmentation
• Human pose estimation

The tutorial offers the possibility to implement and evaluate the learned techniques.

Please note that the course is a direct follow-up course that requires the successfull completion of our main master course  Mutlimedia II (INF-0092) / Machine Learning and Compter Vision (INF-0316).

For more information, please visit the course page or Digicampus.