====== Schedule ====== ===== Lecture times ===== * Mondays and Wednesdays, 11:30-13:00, VH 3006 ===== Lab session ===== Lab Sessions are Mondays and Wednesdays, 16:00-18:00 in LAS 1004. There will not be a lab on Wednesday, September 4th. Information on upcoming lab sessions and lab content can be found below. ===== Weekly Lecture and Assignments Schedule ===== == The following schedule is tentative and will be updated throughout the term to reflect the actual progress of our particular course. Lecture notes will be posted incrementally as material is covered in class. ==
Week Date Lecture Reading Assignment Out Work due
0 September 4 Introduction Textbook Chapter 1 Project None
1 September 9 Image Formation Textbook Chapter 2 None None
September 11 Image Representation 1
Demo Notebooks 		Textbook Sections 3.1-3.3 None None
2 September 16 Image Representation 2
Demo Notebooks 2 		Textbook Sections 3.4-3.5 None None
September 18 Feature Detection 1
Demo Notebooks 3 		Textbook Sections 4.2 None None
3 September 23 Feature Detection 2 Textbook Sections 4.1 Assignment 1 Project White Paper
September 25 Feature Detection 3
Demo Feature Notebooks		 Textbook Sections 4.3 None None
4 September 30 Feature Detection 4 None None
October 2 Image Understanding 1
Saliency and Softmax Demos		 None Assignment 1
5 October 7 Image Understanding 2 None None
October 9 Image Understanding 3 The Evolution of Object Categorization None Project Proposal
- October 14 Reading Week, No Class None None
October 16 Reading Week, No Class None None
6 October 21 Image Understanding 4 None None
October 23 Image Understanding 5
Demos for Gradient Descent and Boundary Problems		 None None
7 October 28 Midterm None None
October 30 Image Understanding 6 - Guest Lecture None None
8 November 4 Stereopsis 1 Assignment 2 Project Site Visit (in Lab)
November 6 Stereopsis 2
Demo Notebooks - Patch Matching 		None Project Site Visit (in Lab)
9 November 11 Stereopsis 3 Textbook Chapter 11 None None
November 13 Motion 1 None None
10 November 18 Motion 2 None Assignment 2
November 20 Final Demos None Project Demos in Class
11 November 25 Final Demos None Project Demos in Class
November 27 Final Demos None Project Demos in Class
12 December 2 Final Demos None Project Demos in Class,
Final Report (deadline extended to Dec. 9)
===== Lab Schedule ===== The following schedule will be updated throughout the course and will provide an explanation of what content each lab will cover prior to the lab date.
Week Date Content Work due in lab
1 September 9/11 Review of Resources: OpenCV and LaTeX None
2 September 16/18 Image Filtering: Template Matching None
3 September 23/25 Assignment 1 Advising None
4 September 30/October 2 Panoramic Image Stitching None
6 October 21/October 23 Deep Learning Introduction None
==Download Links:== Lab 1: {{:eecs_4422_5323_lab_1_resources.pdf|Lab 1 Slides}} {{:lab1_images.zip|Images for Lab 1}} Lab 2: {{:eecs_4422_5323_lab_2_template_matching.pdf|Lab 2 Slides}} {{:lab2_images.zip|Images for Lab 2}} Lab 4: {{:lab_4.pdf|Lab 4 Slides}} [[http://www.cse.yorku.ca/~calden/Lectures/panorama_images.zip|Images for Lab 4]] Lab 5: {{:lab_5_-_deep_learning.pdf|Lab 5 Slides}} {{:lenet_definition.zip|LeNet Definition File}} ===== Assignment Downloads ===== ==Assignment 1== * [[http://www.cse.yorku.ca/~calden/Assignments/Q5_train.zip|Q5 Train]] * [[http://www.cse.yorku.ca/~calden/Assignments/Q5_samples_4422.zip|Q5 Samples 4422]] * [[http://www.cse.yorku.ca/~calden/Assignments/Q5_samples_5323.zip|Q5 Samples 5323]] ==Assignment 2== * [[http://www.cse.yorku.ca/~calden/Assignments/Assignment_2_files.zip|Assignment 2 Files]]