EC ENGR 149
Foundations of Computer Vision
Description: Lecture, four hours; discussion, two hours; outside study, six hours. Recommended requisites: courses 102, 131A, Mathematics 33A. Covers foundations of computer vision from both theoretical and practical perspective. Particular emphasis on classical computer vision, which should be seen as complementary to deep learning. Study is relevant for various majors in the sciences specializing in artificial intelligence, cyberphysical systems and information engineering, robotics, machine learning, perception, and others looking for applications. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Fall 2024 - I love Prof. Kadambi. He explains very abstract and complex concepts in a clear and organized manner. The contents are interesting. The professor is not strict at giving grades, so there is not too much pressure in learning. Overall, EE149 is one of the best courses I have ever taken at UCLA and Prof. Kadambi is one of the best professors at UCLA.
Fall 2024 - I love Prof. Kadambi. He explains very abstract and complex concepts in a clear and organized manner. The contents are interesting. The professor is not strict at giving grades, so there is not too much pressure in learning. Overall, EE149 is one of the best courses I have ever taken at UCLA and Prof. Kadambi is one of the best professors at UCLA.
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