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Computer Vision Tutorial
Home
Environment Setup
Install Conda, keras, Tensorflow
Install OpenCV
Setup AWS GPU
Intro to Computer Vision
Image Classification Pipeline
Pre-processing
Image Segmentation
Features Extraction
Project 1: License Plate Detection
Intro to Deep Learning
Convolutional Neural Networks
Convolutional Layers
Stride and padding
Pooling
Putting it all together
Project 2: MNIST Classifier
Additional Resources
Machine Learning Strategy
CNN Architechture
Object Detection
Object Segmentation
Transfer Learning
What's next? (WIP)
Computer Vision Tutorial
What's next? (WIP)
Learn
Image Augmentation
YOLO or SSD Object Detection (Single-Shot MultiBox Detector):
Siraj tutorial
and
github code
GANs (Generative Adversarial Networks)
Style Transfer
Code
Project 1 (full stack classifier):
Part 1:
How to (quickly) build a deep learning image dataset
Part 2:
Keras and Convolutional Neural Networks
Part 3:
Running a Keras model on iOS (coming soon)
Project 2:
Iceberg Classification challenge
on Kaggle
Read
More CV applications:
The three R’s of computer vision: Recognition, reconstruction and reorganization
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