Term: Fall 2013 Instructor: Prof. Gang Hua
Time: Tuesday 2:00pm – 4:30pm
Building/Room: EAS 330
Office Hour: Wednesday
4:00pm—5:00pm by appointment Office
Hour Location: Lieb
Building/Room 305 Course Assistant:
Yizhou Lin Course Website:
http://www.cs.stevens.edu/~ghua/ghweb/teaching/CS541Fall2013.htm

Course Overview: This course will give an introduction to the
large and diverse field of artificial intelligence. Topics include:
problem solving by search and constraint satisfaction; alpha-beta
search for two-player games; and logic and knowledge representation,
planning, learning and decision theory, statistical machine learning,
and reinforcement learning, etc.

Prerequisites: CS 385 Algorithms or CS 182
Introduction to Computer Science Honors II

Text Books: Stuart Russell and Peter Norvig,
“Artificial Intelligence: A Modern Approach”, Third Edition,
Prentice Hall, December 11, 2009 (Required)

Grading:
The students will be graded based on course participation (10%), four
homework including a midterm project (some of them need programming)
(first 2 and midterm 10%, last one 10% each adding up to 40%), and a
final project/presentation (50%). Final grade: A-- 90% to 100%; B--80%
to 89%; C-- 60% to 79%; F -- < 60%

Late
submission policy:
Exponential penalty -- late for one day loses half, two day loses
another half of the remaining, and so on and so forth.

Topics:

Image Formation:
Cameras, Geometric camera models, Calibration, Radiometry,
Color.

Early Vision:
Linear filters, Edge detection, Texture, Geometry of multiple
views.

Mid-level Vision:
Motion, Segmentation, and Tracking.