Computer Vision

This module explores computer vision, a field of Artificial Intelligence that trains computers to interpret and understand the visual world. It covers techniques such as image recognition, object detection, and deep learning models that enable applications like automated inspection, surveillance, and autonomous driving.

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Szeliski, Richard. “Computer Vision: Algorithms and Applications,” Second Edition, 2021.

Forsyth, David, and Jean Ponce. “Computer Vision: A Modern Approach, 2e”, Pearson, 2012.

Bishop, Christopher M. “Pattern Recognition and Machine Learning,” New York: Springer, 2006.

Goodfellow, I, Bengio, Y, and A. Courville “Deep Learning: Algorithms and Applications”, MIT Press, 2017.

Khan, S., Rahmani, H., Shah, S., and M. Bennamoun,“A Guide to Convolutional Neural Networks for Computer Vision”, Springer Cham, 2018.

Sonka, Milan, Hlavac, Vaclav, and Roger Boyle. “Image Processing, Analysis and Machine Vision,” Chapman & Hall, London, 4th ed.

Gonzalez, Rafael, and Richard Woods, “Digital Image Processing,” Prentice Hall, 2008.

Hartley, Richard, and Andrew Zisserman. “Multiple View Geometry in Computer Vision,” 2nd ed, Cambridge University Press, 2004.