Introduction to Computer Vision . ECE 181
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 systems.
Prerequisites: Upper-division standing in Electrical Engineering, Computer Engineering, Computer Science, Chemical Engineering or Mechanical Engineering.
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Very helpful teacher and makes sure students really understand the material before moving on so ask questions if you have them. Highly suggest attending class as there's not too many books or notes otherwise. Material seems hard, but isn't actually too bad once you get a good understanding of it. Projects were pretty simple and not too long.
His lectures are really good and he answers students questions until everyone understands. I learned a lot in class. The homework could be unclear but he'd clarify in class. The exams were somewhat difficult but doable.
Manjunath is a pretty good professor - every quarter he tries a new course project and they are usually pretty interesting. His class is a fair amount of work, but the material is do-able and the exams aren't too difficult. Very intelligent professor, pretty interesting class. Would recommend.
Cheng-Zhong Qin
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Yogananda Isukapalli
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