Can I read Mastering Computer Vision with TensorFlow 2.x : Build Advanced Computer Vision Applications Using Machine Learning and Deep Learning Techniques on EtoBox?

Mastering Computer Vision with TensorFlow 2.x : Build Advanced Computer Vision Applications Using Machine Learning and Deep Learning Techniques by Krishnendu Kar is a nonfiction available to read on EtoBox.

What is Mastering Computer Vision with TensorFlow 2.x : Build Advanced Computer Vision Applications Using Machine Learning and Deep Learning Techniques about?

Apply neural network architectures to build state-of-the-art computer vision applications using the Python programming language Key Features Gain a fundamental understanding of advanced computer vision and neural network models in use today Cover tasks such as low-level vision, image classification, and object detection Develop deep learning models on cloud platforms and optimize them using TensorFlow Lite and the OpenVINO toolkit Book Description Computer vision allows machines to gain human-level understanding to visualize, process, and analyze images and videos. This book focuses on using TensorFlow to help you learn advanced computer vision tasks such as image acquisition, processing, and analysis. You'll start with the key principles of computer vision and deep learning to build a solid foundation, before covering neural network architectures and understanding how they work rather than using them as a black box. Next, you'll explore architectures such as VGG, ResNet, Inception, R-CNN, SSD, YOLO, and MobileNet. As you advance, you'll learn to use visual search methods using transfer learning. You'll also cover advanced computer vision concepts such as semantic segm

Who reads Mastering Computer Vision with TensorFlow 2.x : Build Advanced Computer Vision Applications Using Machine Learning and Deep Learning Techniques?

Author

Krishnendu Kar

Publisher

Packt Publishing, Limited

Published

2020

Language

EN

ISBN

9781838827069

Category

nonfiction

Subjects

Engineering, Computer Science, Stem