September 16
                    
Lecture 1: Course Introduction
                    
Lecture 2: kNN classifier
September 23
                    
Lecture 3: Computer Vision Concepts
September 30
                    
Finish Lecture 3
                    
Lecture 4: Image Representation
October 7
                    
Lecture 5: Cross Validation
                    
Lecture 6: High Dimensionality
                    
Lecture 7: Linear
and generalized liner classifier
October 14
                    
Paper Discussion:
                    
"Recognizing Action at a Distance"
                    
"80 million tiny images: a large dataset for non-parametric object and scene recognition"
October 21
                    
Finish Lecture 7.
October 28
                    
Lecture 8: Support Vector Machines
November 4
                    
                    
Finish lecture 8 and Paper Discussion:
                    
"Histograms of Oriented Gradients for Human Detection"
                    
"Beyond Bags of Features: Spatial Pyramid Matching
for Recognizing Natural Scene Categories"
November 11
                    
Lecture 9: Boosting
November 18
                    
Paper Discussion:
                    
"Rapid Object Detection using a Boosted Cascade of Simple Features"
                    
"Detecting Pedestrians Using Patterns of Motion and Appearance"
November 25
                    
Lecture 10: Neural Networks
December 2
                    
Finish Lecture 10 and
Paper Discussion:
                    
"ImageNet Classification with Deep Convolutional
Neural Networks"
December 8
                    
Student Paper Presentations from 10:30-11:45 in MC316
December 9
                    
Finish Lecture 10 and
                    
Student Paper Presentations
December 10
                    
Student Paper Presentations from 2-3:30 in MC316
January 19
                    
Student Project Presentations from 12:30-1:30 in MC300
January 20
                    
Student Project Presentations from 11:00-1:30 in MC300