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Course Criteria
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3.00 Credits
(Also offered as ARTS 394 and MA 394.) Introduction to story boarding, modeling, rendering, animation and dynamics. Class uses high-level commercial animation software. Course emphasizes both the development of technical skills and the aesthetic aspects of computer imagery. Not allowed for graduate credit for computer science majors, nor as a technical elective for undergraduate computer science majors.
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3.00 Credits
Mathematical reasoning for computer science. Topics include propositional and first-order logic, group theory, introduction to formal languages and formal models of computation. Restriction: undergraduate. Offered on a CR/NC basis only.
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3.00 Credits
433.] Introduction to Computer Graphics: Scanline Algorithms [ Computer Graphics.] ( 3) (Also offered as ECE 412.) This course is an introduction to the technical aspects of raster algorithms in computer graphics. Students will learn the foundational concepts of 2-D and 3-D graphics as they relate to real-time and offline techniques. Students will develop a video game as a final project to demonstrate the algorithms learned in class. Prerequisite: 361L or ECE 331. {Fall}
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3.00 Credits
Topics include ray-geometry intersections, viewing, lenses, local/global illumination, procedural textures/models, spline curves and surfaces, and statistical integration for realistic image synthesis. Students will write a raytracing renderer from scratch, exploring high performance implementations and realistic rendering. Prerequisite: CS 361L or ECE 331.
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3.00 Credits
Introduction to fundamentals of digital image processing. Specific topics include grey level histograms, geometric/grey level transformations, linear systems theory, Fourier transforms, frequency domain filtering, wavelet transforms, image compression, edge detection, color vision, and binary image morphology. Prerequisite: 357L and (MATH 314 or MATH 321).
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3.00 Credits
Introduces topics in complex adaptive systems, including: definitions of complexity, fractals, dynamical systems and chaos, cellular automata, artificial life, game theory, neural networks, genetic algorithms and network models. Regular programming projects are required. Prerequisite: 251 and MATH 163.
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3.00 Credits
Survey of artificial intelligence exclusive of pattern recognition. Heuristic search techniques, game playing, mechanical theorem proving, additional topics selected by the instructor. Prerequisite: 351L.
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3.00 Credits
Introduction to principles and practice of systems that improve performance through experience. Topics include statistical learning framework, supervised and unsupervised learning, Bayesian analysis, time series analysis, reinforcement learning, performance evaluation and empirical methodology; design tradeoffs. Prerequisite: 362 and STAT 345 and (MATH 314 or MATH 321).
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3.00 Credits
Concepts of intelligence from psychology and computer science. Areas considered include production systems, expert systems, computer assisted instruction, models for semantics and human cognitive processes from pattern recognition to output systems. Includes a project.
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3.00 Credits
A study of the design concepts of major importance in modern computers. Topics will include microprogramming, language-directed computers, parallel processors and pipeline computers. Emphasis will be placed on the relationship of architecture to programming issues. Prerequisite: 341L.
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