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CSCI 1430 - Computer Vision |
How can we program computers to understand the visual world? This course treats vision as inference from noisy and uncertain data and emphasizes probabilistic and statistical approaches. Topics may include perception of 3D scene structure from stereo, motion, and shading; segmentation and grouping; texture analysis; learning, object recognition; tracking and motion estimation. Strongly recommended: basic linear algebra, calculus, and probability.
0.000 OR 1.000 Credit hours 0.000 OR 1.000 Lecture hours Levels: Graduate, Undergraduate Schedule Types: Discussion Section/Conference, Primary Meeting Computer Science Department Prerequisites: Undergraduate level CSCI 0160 Minimum Grade of S or Undergraduate level CSCI 0180 Minimum Grade of S or Undergraduate level CSCI 0190 Minimum Grade of S |
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