227-0085-11L Projects & Seminars: Deep Learning for Image Manipulation (DLIM)
| Semester | Spring Semester 2022 |
| Lecturers | L. Van Gool |
| Periodicity | every semester recurring course |
| Course | Does not take place this semester. |
| Language of instruction | English |
| Comment | Only for Electrical Engineering and Information Technology BSc. The course unit can only be taken once. Repeated enrollment in a later semester is not creditable. |
| Abstract | The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work. |
| Learning objective | Deep Learning – Image Manipulation – Image Enhancement – Image Restoration – Style Transfer – Image to Image Translation – Generative Models – TensorFlow/PyTorch – Projects With the advent of deep learning tremendous advances were achieved in numerous areas from computer vision, computer graphics, and image processing. Using these techniques, an image can be automatically manipulated in various ways with high-quality results, often fooling the human observer. Deep learning based image processing and manipulation are being applied in a vast number of emerging technologies, including image enhancement in smartphone cameras, automated image editing, image content creation, graphics, and autonomous driving. This course focuses on the fundamentals of deep learning and image manipulation. Students will learn the tools to implement and develop deep learning solutions for a variety of image manipulation tasks. The course will end with a 4 weeks project where the students can target a specific application scenario. The course will be taught in English. |