Computer Vision and Deep Learning

4 credits

Covers deep learning algorithms and architectures for computer vision with emphasis on end-to-end models and practical implementation. Explores neural network training and optimization, regularization, and approaches such as convolutional neural networks, recurrent neural networks, variational autoencoders, and generative adversarial networks. Includes ethical considerations in computer vision applications. Prerequisite: CSE D 501. Offered: W.