Introduction to vision on sensing and frameworks

This course offers an introduction to computer vision with a focus on deep learning, specifically Convolutional Neural Networks (CNNs). It is tailored for professionals in fields like robotics and AI, providing essential skills in camera calibration and applying deep learning techniques.

Target audience: Professionals in robotics, AI, and related fields looking to integrate computer vision into their work.

Prerequisite-knowledge: Basic programming skills and a foundational understanding of robotics.

Course content: The course covers core concepts of deep learning for vision systems, including practical applications and self-paced online modules. Participants will gain hands-on experience through exercises and tutorials.

How the course will be conducted: Self-study through online materials, with a total of 15 hours of work required to complete the course.

To pass the course you need to: Complete the required exercises and quizzes to demonstrate understanding of the materials.

Teacher:

Rucha Sawlekar: Rucha Sawlekar is a postdoctoral researcher in Robotics and AI at Luleå University of Technology. Her work focuses on neuromorphic computing and sensor fusion for subterranean environments. She is involved in several European and VINNOVA-funded projects, such as OptiScrap and REBOOT Skills.