This course is the first semester course of a two-semester sequence providing foundational skills in computer programming required in the field of Imaging Science. This course is focused on mastery of fundamental of Python and c++ computer programming skills and their application to problems in Imaging Science.

This course will cover a wide range of current topics in modern image processing and computer vision. Topics will include introductory concepts in supervised and unsupervised machine learning, linear and nonlinear filtering, image enhancement, supervised and unsupervised image segmentation, object classification, object detection, feature matching, image registration, and the geometry of cameras. Assignments will involve advanced computational implementations of selected topics from the current literature in a high-level language such as Python, MATLAB, or Julia and will be summarized by the students in written technical papers. The course requires computer programming, linear algebra, and calculus.

This course is a cooperative education experience for graduate imaging science students.

This is a graduate-level course on a topic that is not part of the formal curriculum. This course is structured as an ordinary course and has specific prerequisites, contact hours, and examination procedures.

Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.

Continuation of Thesis