This course provides a comprehensive introduction to computer vision, focusing on enabling machines to interpret and analyze visual information from the world. Students will explore the foundational principles, mathematical underpinnings, and cutting-edge techniques used in computer vision systems. Topics include image processing, feature extraction, object recognition, and advanced Deep Learning methods for vision tasks. Through hands-on programming assignments and projects, students will build practical skills to design, implement, and optimize computer vision applications. By the end of the course, students will be prepared to tackle real-world challenges in fields such as autonomous systems, medical imaging, and augmented reality. Hands-on programming assignments will familiarize students with Deep Learning frameworks such as TensorFlow, PyTorch, or Keras and prepare them to build and train neural network models. A final project will allow students to apply their skills to real-world problems of personal interest.
P: COMP SCI 362 with at least a C grade
Fall Only.