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Deep Learning for Computer Vision

Deep Learning for Computer Vision

By : Shanmugamani
3.2 (22)
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Deep Learning for Computer Vision

Deep Learning for Computer Vision

3.2 (22)
By: Shanmugamani

Overview of this book

Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation.
Table of Contents (12 chapters)
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Deployment of models in devices


TensorFlow models can be deployed in mobile devices too. Mobile devices include smartphones, drones, home robots and so on. Billions of smartphones can have applications of computer vision which can use deep learning. One can take a photo and search, stream a video with scenes tagged and so on. Deploying in mobile devices means that the deep learning model is present on the device and inference happens on the device. Models deployed on the device helps in privacy issues. In the following topics, we will discuss how to deploy them across various mobile platforms.

Jetson TX2

Jetson TX2 is an embedding device supplied by NVIDIA specifically efficient AI computing. Jetson TX2 is lightweight, compact and hence suitable for deployment in drones, public places and so on. It also ships preinstalled TensorRT which is a runtime for TensorFlow. You can buy Jetson and flash install Ubuntu, CUDA, CUDNN before installing TensorFlow. Clone https://github.com/jetsonhacks/installTensorFlowTX2...

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