As humans, we see a million objects around us every day, in different scenarios. For humans, describing a scene is usually a trivial task: something we do without even taking a noticeable amount of time to think. But it is a huge task for machines to comprehend the elements and scenarios presented to it in visual media such as images or videos. However, for several applications of artificial intelligence (AI), it is useful to have the capability of comprehending such images in the computer system. For example, it would be of immense help to visually impaired people if we could devise machines that could translate their surroundings into audio in real time. Also, there has been a constant effort from researchers to generate captions for images and videos in real time, so as to improve the accessibility of content presented on websites...
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
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Overview of this book
Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more.
With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment.
By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.
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Current Title:
Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter
Table of Contents (13 chapters)
Preface
Introduction to Deep Learning for Mobile
Free Chapter
Mobile Vision - Face Detection Using On-Device Models
Chatbot Using Actions on Google
Recognizing Plant Species
Generating Live Captions from a Camera Feed
Building an Artificial Intelligence Authentication System
Speech/Multimedia Processing - Generating Music Using AI
Reinforced Neural Network-Based Chess Engine
Building an Image Super-Resolution Application
Road Ahead
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