This course teaches how to implement a Super-Resolution Generative Adversarial Network (SRGAN) from scratch. The learning outcomes include understanding the SRGAN model, implementing the model, incorporating the VGG Loss Term, reviewing training processes, utilities, and configuration files. The teaching method is through a YouTube video tutorial. The intended audience for this course is individuals interested in deep learning, specifically in the field of image super-resolution using GANs.
Overview
Syllabus
​ - Introduction and Overview
- Model implementation
- VGG Loss Term
- Quick review of train, utils, config file
- Ending
Taught by
Aladdin Persson
