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<pclass="m-0">Overview of computer vision problems and techniques for analyzing the content of images and video. Topics include image formation, alignment and warping; stereo vision; feature extraction, matching, and tracking; deep learning-based object detection, recognition, and segmentation; and case studies of practical vision systems.</p>
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<pclass="m-0">A lecture course that surveys computational neuroscience, which is a branch of neuroscience that employs mathematical models, theoretical analysis, and abstractions of the brain to understand the principles that govern development, structure, physiology, and cognitive abilities of the nervous system. We will cover both classical (e.g., GLM, LIF, …</p>
<ahref="/teaching/2026-winter-cs281b/" itemprop="url">CS/ECE-281B: Advanced Topics in Computer Vision</a>
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<pclass="m-0">Overview of computer vision problems and techniques for analyzing the content of images and video. Topics include image formation, edge detection, image segmentation, pattern recognition, texture analysis, optical flow, stereo vision, shape representation and recovery techniques, issues in object recognition, and case studies of practical vision …</p>
<pclass="m-0">A lecture course that surveys computational neuroscience, which is a branch of neuroscience that employs mathematical models, theoretical analysis, and abstractions of the brain to understand the principles that govern development, structure, physiology, and cognitive abilities of the nervous system. We will cover both classical (e.g., GLM, LIF, …</p>
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