Applied Computer Vision

3 credits

Topics include image fundamentals (formation, geometrical transformation, convolution/filtering, edge detection), image features (gradients, HoG, corners, SIFT), image registration, image classification, object detection, segmentation and clustering, motion estimation, image synthesis (GANS and Diffusion Models). The primary focus is practical applications with Python using OpenCV and deep learning libraries (Keras, Tensorflow, PyTorch). *Note: Students may receive credit for one of ENEL 866 or ENEL 890AQ.*