TensorFlow 2.0 Computer Vision Cookbook
This book covers recipes for solving various computer vision tasks using TensorFlow, taking you through all the tips and tricks you need to overcome any challenges that you may face while building various computer vision applications. You will discover machine learning techniques to solve problems in image processing, feature extraction, and more.
Offered by
Difficulty Level
Intermediate
Completion Time
18h4m
Language
English
About Book
Who Is This Book For?
This book is for computer vision developers and engineers, as well as deep learning practitioners looking for go-to solutions to various problems that commonly arise in computer vision. You will discover how to employ modern machine learning (ML) techniques and deep learning architectures to perform a plethora of computer vision tasks. Basic knowledge of Python programming and computer vision is required.
TensorFlow 2.0 Computer Vision Cookbook
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 18h4m total length
Getting Started with TensorFlow 2.x for Computer Vision
Performing Image Classification
Harnessing the Power of Pre-Trained Networks with Transfer Learning
Enhancing and Styling Images with DeepDream, Neural Style Transfer, and Image Super-Resolution
Reducing Noise with Autoencoders
Generative Models and Adversarial Attacks
Captioning Images with CNNs and RNNs
Fine-Grained Understanding of Images through Segmentation
Localizing Elements in Images with Object Detection
Applying the Power of Deep Learning to Videos
Streamlining Network Implementation with AutoML
Boosting Performance
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