Department of Computer Science Pattern Recognition (Topics in Artificial Intelligence, Fall 2008) 4005-759-01 (Calendar Description)

Home --- Syllabus --- Schedule & Slides --- Assignments --- Resources

Instructor: Richard Zanibbi, Office hours: 2-3:50pm Tuesdays and Thursdays, Room 70-3551 (Golisano College)
Lectures: 10-11:50am Tuesdays and Thursdays, Room 70-2590 (Golisano College)

Resources

Writing and the Research Process

Notes on what is expected for papers in this class: Some Notes on Academic Writing for Computer Science.

The following references are very useful, and quite cheap to purchase. All three of these books are also available in the Wallace Library.

• Writing for Computer Science, 2nd edition, by Justin Zobel. This is an excellent introduction to writing research papers and theses. The book also discusses the process of research for computer scientists.
• The Elements of Style, Fourth Edition by Strunk and White. A short, cheap, and classic reference on writing clearly and concisely.
• (An additional reference, for your thesis/project) Writing the Doctoral Dissertation by Gordon Davis and Clyde Parker. This is a short reference on the thesis process, including the planning and completion of a thesis (whether PhD or Master's). The book includes material on drafting summaries for possible thesis topics that is particularly useful.

Books on Pattern Recognition

The books below marked with an asterisk (*) will be available for 2-hour loans from the reserve desk in the library. Our library has many other related sources; try searching the RIT library database using "pattern recognition" as the subject or title. Don't forget about inter-library loans if you can't find what you need online or in the library.

• C. Bishop. (2006) Pattern Recognition and Machine Learning, Springer. *
• C. Bishop. (1995) Neural Networks for Pattern Recognition, Oxford University Press. *
• L. Kuncheva. (2004) Combining Pattern Classifiers, Methods and Algorithms, Wiley. *
• A. Jain and R. Dubes. (1988) Algorithms for Clustering Data, Prentice-Hall, 1988. (if you can find a copy...)
• K. Fukunaga. (1972) Introduction to Statistical Pattern Recognition, Academic Press. *
• P. Devijver and Y. Kittler. (1982) Pattern Recognition: A Statistical Approach, Prentice-Hall. *
• K.S. Fu. (1982) Syntactic Pattern Recognition and Applications, Prentice-Hall. *
• S. Watanabe. (1985) Pattern Recognition: Human and Mechanical, Wiley. *
• R.J. Schalkoff. (1992) Pattern Recognition: Statistical, Structural, and Neural Approaches, Wiley.*

Software

• PRTools toolbox for MATLAB, developed at DELFT in the Netherlands.
• Ludmila Kuncheva's MATLAB code illustrating examples from her book, "Combining Pattern Classifiers."
• lush, the Lisp Universal SHell. Includes implementations of various neural net algorithms (including the LeNet5 convolutional neural net) along with many other neural net/machine learning algorithms.
• The Intel Open Source Computer Vision Library (written in C++; a new book on using OpenCV will soon be available: link).
• The Torch machine learning library (written in C++).