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Electrical Engineering and Computer Science

New Graduate Courses Available for Fall 2008

Published on May 1st, 2008 by Michelle Ward

The EECS Department will be offering two new graduate courses beginning the Fall 2008, Advanced Database Systems and Computer Vision, both of which are detailed below.


EECS 700 – Advanced Database Systems
MW 12:30-1:45 in 3154 Learned

An advanced course in data engineering for graduate students. The course materials will be drawn from classic and most recent database literature. The course will cover (1) “classics” of relational database systems; and (2) state-of-the-art in data engineering research. We will spend more time on the second part. Possible topics include: query evaluation and optimization; indexing; data integrity and concurrency control; distributed databases; spatial databases; database and information retrieval; XML and semi-structured databases; security and privacy; web services and AJAX; etc.

Students will have to read research papers chosen from a list of preferred topics, present to the class or write critical reviews, participate in class discussion, as well as write a comprehensive survey or a mini-project paper in a selected area.

Prerequisites: EECS 647 or equivalent, or consent of instructor.

Papers and instructor’s slides will be made available. No text is required. However, any of the following books may be used as reference:

  • Database Management Systems (3rd Edition), by Raghu Ramakrishnan and Johannes Gehrke. McGraw-Hill, 2002. ISBN: 0072465638
  • Database Systems: The Complete Book, by Hector Garcia-Molina, Jeffrey D. Ullman, and Jennifer Widom. Prentice Hall. 2002. ISBN: 0130319953

 


EECS 841: Computer Vision (3)
MWF 3:00-3:50, LEA 1131

The objective of this course is to give students a hands on introduction to the fundamentals of computer vision. Topics include: Image Formation, Image Segmentation, Binary Image Analysis, Edge Detection, Line Drawing Interpretation, Shape from Shading, Motion Analysis, Stereo, Shape Representation, and Object Recognition.

Prerequisites: Graduate standing and permission of instructor