Introduction to Computer Vision II

4 credits

This course covers advanced topics needed to apply computer vision in industry or follow current research. Example topics include real-time systems for 3-D computer vision, machine learning tools such as support-vector machine (SVM) and boosting for image classification, and deep neural networks for object detection and semantic segmentation. Prerequisites: CSE 152A or CSE 152 or CSE 166; Python programming experience recommended; restricted to students within the CS25, CS26, CS27, CS29, and EC26 majors. All other students will be allowed as space permits.