This course introduces selected topics of recent technologies and algorithm related to image processing and imaging systems. (Prerequisite: EE432, EE535)
This course introduces fundamentals of multirate digital signal processing, such as decimation, expansion, theory, and design of multirate filter banks, wavelet transform, and applications of multirate signal processing.
This course explores the theory and methodologies used to interpret images and videos in terms of semantic content. Techniques from pattern recognition are introduced and discussed to explain how to apply them for image understanding. (Prerequisite: EE535)
This course will explore the principles, models, and applications of computer vision. The course consists of five parts: image formations and image models; generic features, such as edges and corners, from images; the multiple view analysis to recover three-dimensional structure from images; segmentation of images and tracking; the object recognition methodologies. (Prerequisite: EE535)
This course is designed to introduce several medical image systems and related applications based on various image processing techniques. Topics include image reconstruction algorithms, X-ray CT, single photon emission CT, positron emission tomography, magnetic resonance imaging, ultrasound imaging, and related post-processing techniques.
The goal of this course is to provide the theoretical and technical basis required to design and implement speech recognition algorithms or systems. The topics include acoustic-phonetic characterization, speech processing techniques for speech recognition, pattern comparison techniques, theory and implementation of HMMs, searching techniques for continuous speech recognition, and other related implementation issues. (Prerequisite: EE432)