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 by
Difficulty Level
Intermediate
Completion Time
14h20m
Language
English
About Book
Who Is This Book For?
This book is for computer vision professionals, image processing professionals, machine learning engineers and AI developers who have some knowledge of machine learning and deep learning and want to build expert-level computer vision applications. In addition to familiarity with TensorFlow, Python knowledge will be required to get started with this book.
Mastering Computer Vision with TensorFlow 2.x
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 14h20m total length
Computer Vision and Tensorflow Fundamentals
Content Recognition using Local Binary Pattern
Face Recognition and Tracking using Viola Jones Algorithm & OpenCV
Deep learning on images
Neural Network Architecture & Models
Visual Search using Transfer Learning
Object Detection using YOLO
Semantic Segmentation and Neural Style Transfer
Action Recognition using Multitask Deep Learning
Object Classification and Detection using RCNN
Deep Learning on Edge Devices with GPU/CPU Optimization
Cloud Computing Platform for Computer Vision
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