COURSE

ROAS4760

Machine Learning on Images

Systems Hub / Robotics and Autonomous Systems · 3 Credits

This course introduces methods to process images on a computer. Topics include the formation and quantification of digital images, morphological image processing, image enhancement in the spatial and frequency domain, image restoration, color image processing, image compression, image segmentation, image representation and description, the image pattern classification using classic machine learning approaches, such as minimum-distance, and Bayes classifiers, Support Vector Machine et al., the modern approaches implemented using deep neural networks. This course provides a new perspective of comparing image processing technique to human vision system in terms of information perception and decision making. Students are expected to obtain knowledge of digital image processing, and hands-on experience on programming and presentation skill through the final project. This course is mathematics-oriented. It requires basic knowledge of linear algebra, calculus and linear filtering. Familiarity with the programming language MATLAB is needed.