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Lecture is held on Tuesdays and Thursdays from 11:15-12:05 in Phillips 407. Lectures are mandatory. It is important that you attend, because we will cover items in lecture that we will not cover elsewhere in the course.

Lecture notes

Lecture notes will be posted here after each class. They can be downloaded in PDF or PPT format. If you find any of these links missing, or cannot open any of the files, please send email to the course staff.

Lecture Date Contents

0 1/20 Matlab Introduction
PDF
1 1/20 Robots: Cute but Dumb PPT PDF
2 1/22 Finding Red Pixels, Part 1 PPT PDF
3 1/27 Finding Red Pixels, Part 2 PPT PDF
4 1/29 Robustness and speed PPT PDF
5 2/3 Sorting and selection PPT
PDF
6 2/5 Sorting and selection, Part 2 PPT
PDF
7
2/10 Blobs and graphs
PPT
PDF
Notes on Big-O
8
2/12 Connected components and graph traversal
PPT
PDF
9
2/17 Breadth-first and depth-first graph traversal
PPT
PDF
10
2/19 Linked lists
PPT
PDF
11
2/24 Linked lists and memory allocation
PPT
PDF
Study Guide for Prelim 1
12
3/3 Polygons and convex hull
PPT
PDF
13
3/5 Interpolation
PPT
PDF
14
3/10 Image transformations
PPT
PDF
15
3/12 Image transformations, Part 2
PPT
PDF
16
3/24 Object recognition
PPT
PDF
17
3/26 Feature-based object recognition
PPT
PDF
18
3/31 Finding transformations
PPT
PDF
19
4/2 Optimization and least squares
PPT
PDF
Study Guide for Prelim 2
20
4/9 Markov chains
PPT
PDF
21
4/14 Markov chains -- Part 2
PPT
PDF
22
4/21 Author recognition
PPT
PDF
23
4/23 Clustering and greedy algorithms
PPT
PDF
23
4/28 Clustering and greedy algorithms -- Part 2
PPT
PDF
Study Guide for Prelim 3
 

If you have any questions that you would like answered over email, please direct them to cs1114-staff-l@lists.cs