Lab Course - Mobile Computer Vision

Aim of this Lecture

In this lab course, students develop a first understanding of computer vision models based on neural networks and are supposed to learn a little bit of the involved tools including

  • Python
  • Data Mining Problems and scikit-learn
  • Deep Learning and Tensorflow
  • Convolutional Neural Networks in Practice
  • FPGAs, GPUs, and modern SoCs
  • Methods for accellerated Deep Learning Inference

This backrgound is learned during the semester with weekly assignments (videos, book chapters) followed by a weekly discussion and question session (e.g. inverted classroom).

After having complete this corpus of preparations, students are encouraged to design, train, and deploy their own deep learning computer vision systems to current FPGAs for inference.

© 2020 M. Werner