Why we need GANs for image manipulation – Michal Hradiš

  Machine learning

Image processing certainly did not miss out on the big convolutional network revolution. Networks are at the core of state-of-the-art methods in image deblurring, superresolution, motion estimation, and even in such mundane tasks as image compression. Compared to more traditional approaches, networks can be trained for specific types of images, don’t require deep understanding of complex mathematics, and they can even hallucinate realistic image details.

In this talk, I will show you how efficient image processing networks can be built and trained. I will explain why the hell do we need Generative Adversarial Networks and how they relate to human perception. The presented ideas will be demonstrated on real world image enhancement applications. You’ll get a chance to experiment with them at home using provided TensorFlow code.

Language: English

- Talk
- Discussion
- Networking (ImpactHub)

Machine Learning Meetups (MLMU) is an independent platform for people interested in Machine Learning, Information Retrieval, Natural Language Processing, Computer Vision, Pattern Recognition, Data Journalism, Artificial Intelligence, Agent Systems and all the related topics. MLMU is a regular community meeting usually consisting of a talk, a discussion and a subsequent networking. At the end of the year 2016, MLMU spread also to Brno and Bratislava.