Machine Learning for Visual Data Analysis

Module code: ECS797P

Credits: 15.0
Semester: SEM2

Contact: Dr Ziquan Liu

The module will cover the following topics:

The Discrete Fourier Transform and the frequency content of images.
The design and use of Gabor filters.
Principal Component Analysis for denoising and compression.
Unsupervised classification via feature space clustering.
Texture segmentation with Gabor filters.

Connected course(s): UDF DATA
Assessment: 60.0% Examination, 40.0% Coursework
Level: 7