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 and machine learning techniques as applied to computer vision problems, including: stereo vision, motion estimation, object and face recognition, image registration and segmentation. Topics include regularization, probabilistic inference, information theory, Gaussian Mixture Models, Markov-Chain Monte Carlo methods, importance sampling, Markov random fields, principal and independent components analysis, probabilistic deep learning methods including variational models, Bayesian deep learning.

Terms: Fall 2024

Instructors: Arbel, Tal (Fall)

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