CSC 382: Applied Image Analysis

Image analysis from classical computational imaging techniques to deep learning techniques. Fundamentals of computational image analysis in terms of image information extraction and modeling of image patterns. Specific topics include, but are not limited to: image segmentation, multi-scale representation, shape analysis, texture analysis, Fourier analysis, wavelets, Gabor and fractal analysis, and template matching. Deep learning models to extract image representations automatically. Classical and deep learning imaging techniques applied and compared in the context of different image analysis tasks such as image representation, segmentation, classification, retrieval, and object recognition. Applications of these techniques for autonomous driving, biometrics, sports analytics, smart and connected communities, and biomedical and health informatics.