Lab in signal and image processing

Summary

These lab sessions are hands-on exercises focusing on the basics of image processing and deep learning. The main objective is to learn how to use some important image processing libraries, namely OpenCV, numpy and TensorFlow, to perform image analysis tasks.

Content

Keywords

image processing, object detection, object tracking, deep learning, computer vision.

Learning Prerequisites

Required courses

image processing courses

Learning Outcomes

By the end of the course, the student must be able to:

• Create complete image processing pipelines for real problems
• Decide which methods and tools to use in specific cases
• Implement them in common software libraries

Transversal skills

• Use a work methodology appropriate to the task.
• Plan and carry out activities in a way which makes optimal use of available time and other resources.
• Demonstrate a capacity for creativity.

Teaching methods

No dedicated lecture session for this course. All interactions will be done via Moodle and E-mails. TA office hours are available for each assignment on request.

Assessment methods

Graded assignments

Resources

Moodle Link

• https://go.epfl.ch/EE-490_f