Workshop 1: Introduction to Image Processing, Classical Machine Learning, and Deep Learning

Day 1

9:00am-9:10am	Welcome and Preliminaries
9:10am-10:00am	Section 1: Working with Grayscale Images
10:00am-10:10am	Break
10:10am-11:00am	Section 1: Working with Grayscale Images (cont.)
11:00am-11:50am	Lunch Break
11:50am-12:40pm	Section 2: Working with Color Images
12:40pm-12:50pm	Break
12:50pm-1:40pm	Section 3: Transforming Images
1:40pm-1:50pm	Break
1:50pm-2:40pm	Section 3: Transforming Images (cont.)
2:40pm-2:50pm	Break
2:50pm-3:50pm	Section 4: Filtering Images
3:50pm-4:00pm	Recap

Day 2

9:00am-9:10am	Welcome and Preliminaries
9:10am-10:00am	Section 1: Working with the CalTech101 Dataset
10:00am-10:10am	Break
10:10am-11:00am	Section 2: Feature Extraction
11:00am-11:50am	Lunch Break
11:50am-12:40pm	Section 2: Feature Extraction (cont.)
12:40pm-12:50pm	Break
12:50pm-1:40pm	Section 3: Setting up a Feature Matrix
1:40pm-1:50pm	Break
1:50pm-2:40pm	Section 4: Classification
2:40pm-2:50pm	Break
2:50pm-3:50pm	Section 4: Classification (cont.)
3:50pm-4:00pm	Recap

Day 3

9:00am-9:10am	Welcome and Preliminaries
9:10am-10:00am	Section 1: Working with the MNIST Dataset
10:00am-10:10am	Break
10:10am-11:00am	Section 2: Data Preprocessing (Dimensionality Wrangling)
11:00am-11:50am	Lunch Break
11:50am-12:40pm	Section 3: Building and Training a CNN for MNIST
12:40pm-12:50pm	Break
12:50pm-1:40pm	Section 4: Building and Training a CNN for MNIST (cont.)
1:40pm-1:50pm	Break
1:50pm-2:40pm	Section 5: Testing the Trained CNN
2:40pm-2:50pm	Break
2:50pm-3:50pm	Section 6: Transfer Learning for MNIST
3:50pm-4:00pm	Recap

Workshop 2: Advanced Topics in Deep Learning

Day 1

9:00am-9:10am	Welcome and Preliminaries
9:10am-10:10am	Section 1: Printed Summaries of Network Architectures
10:10am-10:20am	Break
10:20am-11:00am	Section 2: Visualizing Activations of Neurons
11:00am-11:50am	Lunch Break
11:50am-1:00pm	Section 2: Visualizing Activations of Neurons (cont.)
1:00pm-1:10pm	Break
1:10pm-2:00pm	Section 3: Inputting New and Different Data to a Trained Network
2:00pm-2:10pm	Break
2:10pm-3:30pm	Section 4: The VGG16 architecture
3:30pm-4:00pm	Catchup/Recap

Day 2

9:00am-9:10am	Welcome and Preliminaries
9:10am-10:00am	Section 1: Activation Maximization
10:00am-10:10am	Break
10:10am-11:00am	Section 2: YOLO-v3 for Object Detection
11:00am-11:50am	Lunch Break
11:50am-12:40pm	Section 3: Style Transfer
12:40pm-12:50pm	Break
12:50pm-1:40pm	Section 4: Generative Adversarial Networks
1:40pm-2:30pm	Catchup/Recap/Workshop Evaluation