ECSE 626 Statistical Computer Vision (4 credits)

Offered by: Electrical & Computer Engr (Faculty of Engineering)

Administered by: Graduate Studies


Electrical Engineering : An overview of statistical techniques as applied to computer vision and image processing. Topics include regularization, Kalman filtering, Markov-Chain Monte Carlo methods, importance sampling and particle filtering, Markov Random fields, parameter estimation, mean-field techniques, stochastic and deterministic annealing, principal and independent components analysis.

Terms: This course is not scheduled for the 2019-2020 academic year.

Instructors: There are no professors associated with this course for the 2019-2020 academic year.