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Mastering Computer Vision with TensorFlow 2.x

You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.

Offered byPackt Logo

Difficulty Level
Intermediate
Completion Time
14h20m approx.
Language
English
Certification
Not available

About Course

Book Content

chapters 14h20m total length

1. Computer Vision and Tensorflow Fundamentals
2. Content Recognition using Local Binary Pattern
3. Face Recognition and Tracking using Viola Jones Algorithm & OpenCV
4. Deep learning on images
5. Neural Network Architecture & Models
6. Visual Search using Transfer Learning
7. Object Detection using YOLO
8. Semantic Segmentation and Neural Style Transfer
9. Action Recognition using Multitask Deep Learning
10. Object Classification and Detection using RCNN
11. Deep Learning on Edge Devices with GPU/CPU Optimization
12. Cloud Computing Platform for Computer Vision

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