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Artificial Intelligence and Machine Learning
Description: This course introduces the principles and techniques of computer vision for enabling machines to interpret and analyze visual data. Topics include image representation, feature extraction, filtering, geometric vision, object detection and recognition, convolutional neural networks, and deep learning-based vision models. Students implement and evaluate vision algorithms using real-world image and video data, and analyze challenges related to robustness, scalability, bias, and ethical use. Letter grade only.
Units: 3
Sections offered: Spring 2027
Prerequisite: AIBS: AIML 370, CSBS: CS 249
Artificial Intelligence and Machine Learning
Term : Fall 2026
Catalog Year : 2026-2027
AIML 469 - Computer Vision
Description: This course introduces the principles and techniques of computer vision for enabling machines to interpret and analyze visual data. Topics include image representation, feature extraction, filtering, geometric vision, object detection and recognition, convolutional neural networks, and deep learning-based vision models. Students implement and evaluate vision algorithms using real-world image and video data, and analyze challenges related to robustness, scalability, bias, and ethical use. Letter grade only.
Units: 3
Sections offered: Spring 2027
Prerequisite: AIBS: AIML 370, CSBS: CS 249