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