Introduction to Computer Vision

Day – 1

1. Traditional Computer Vision methodologies
2. Computer vision in our day-to-day life.
3. History of Computer vision
4. What’s an image?
5. Image Transformations.
6. Sobel Filters.

Day – 2

1. OpenCV Hands-On
2. Reading Image
3. Writing on Image
4. Background Subtraction
5. Invisible clock
6. Image Transformations
7. Face Detection
8. Template Matching
9. On Air-Drawing

Day – 3

1. Convolutional Neural Networks
2. Intro Machine Learning
3. How CNN Works
4. Convolution 
5. Pooling
6. Strides
7. Browser Demo’s
8. Basic CNN Implementation
9. CNN Architectures overview
10. 2012-AlexNet
11. 2014-VGGNet
12. 2015-ResNet
13. 2020-FixEfficientNet-L2.

Day – 4

1. Computer Vision Project Workflow. (Tensorflow Implementation)
2. Data Collection
3. Data Pre-processing
4. Data Augmentation
5. Splitting data
6. Training model
7. Evaluating model
8. Transfer Learning

Day – 5

1. Computer Vision Application (Advanced concepts)
2. Object Detection 
3. One-Shot Learning 
4. Face Recognition 
5. Pose Estimation
6. Image Segmentation 
7. Image Captioning 
8. Further Learning Resource

About the Instructor:

Hi, I am Maithreyan Kesavan. I am a Machine learning Facilitator, and I have conducted hands-on ml workshops in institutions across the nation.
Building and organizing Tensorflow User Group Coimbatore. Following are my achievements

• Facilitator – Explore ML academy program google AI

• Co-organizer TFUG
• 2 Years of Experience in ML