CS 541 Artificial Intelligence

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.
High-Level Vision: Model-based vision, Pose estimation, Appearance-based vision, Generic Object Recognition

Schedule:

Computer Vision and Artificial Intelligence

Gang Hua, Ph.D.

Principal Researcher/Research Manatger

Microsoft Research Asia

firstnamelastname AT gmail.com

CS 541 Artificial Intelligence