English

If sufficient demand

This course will cover advanced topics in computer vision with a focus on machine learning,

The course is focused on machine learning methods and paradigms that are used in modern computer vision.

Understand advanced concepts and techniques in machine learning that are used in computer vision.
Understand and discuss the current state-of-the-art and future directions in machine learning-based methods for computer vision.
Be familiar with common network architectures, losses and datasets used in the field.

Be able to apply common machine learning techniques used in computer vision.
Be able to analyse and critique recent research papers in the field.
Be able to apply and understand common evaluation methodologies and benchmarking approaches.

Seminars

Self-study literature review

Seminars given by participants

Failed, pass

The course participants are assumed to have research experience in a topic relevant for the course.

The course is limited to 12 participants.

Preference is given to students admitted to the research subjects Mathematics (TEFMAF00), Numerical Analysis (TEEDAFNA) och Mathematical Statistics (TEFMSF00).

 

Scientific articles that highlight both the history and current research frontier within the field.

FMA325F

2024-05-07

Maria Sandsten