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Computer Vision and Image Processing
The Department of Electrical and Computer Engineering has established itself as a world leader within the science of Computer Vision and Image Processing. Particularly, within the understanding of face perception, pattern recognition and their corresponding computer design elements. ECE researchers also represent one the few international groups offering expertise in human cognition and computational models for Artificial Intelligence. Their focus is to reveal the algorithms of the brain through the discriminatory analysis of Big Data – a modern and popular keyword for the processing and understanding of vast amounts of information.
ECE Computer Vision courses explore the methods for acquiring, processing, analyzing and understanding images and high-dimensional data from the real world, in order to produce numerical or symbolic information. This field is concerned with the theory behind artificial systems that extract information from images. The image data can take many forms, such as video sequences, views from multiple cameras, or multi-dimensional data from a medical scanner. As a technological discipline, computer vision also seeks to apply its theories and models toward the construction of systems.
ECE image processing courses show students how to apply mathematical operations to images in order to enhance understanding of their relatable characteristics or parameters. The science behind this usually refers to digital image processing, but optical and analog image processing also are possible.
Closely related to image processing area, is the field of computer graphics. Here, images are manually made from physical models of objects, environments, and lighting, instead of being acquired from natural scenes, as in most animated movies.
The modern career market for Computer Vision and Image Processing is wildly vibrant. Graduates have landed in the movie industry doing vision and graphics for Disney, found roles at Google, Apple or SnapChat, joined communication roles at Intel or IBM, or taken up software roles at Amazon.