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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

You're reading from   Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter Build scalable real-world projects to implement end-to-end neural networks on Android and iOS

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Length 380 pages
Edition 1st Edition
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Authors (2):
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Rimjhim Bhadani Rimjhim Bhadani
Author Profile Icon Rimjhim Bhadani
Rimjhim Bhadani
Anubhav Singh Anubhav Singh
Author Profile Icon Anubhav Singh
Anubhav Singh
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models FREE CHAPTER 3. Chatbot Using Actions on Google 4. Recognizing Plant Species 5. Generating Live Captions from a Camera Feed 6. Building an Artificial Intelligence Authentication System 7. Speech/Multimedia Processing - Generating Music Using AI 8. Reinforced Neural Network-Based Chess Engine 9. Building an Image Super-Resolution Application 10. Road Ahead 11. Other Books You May Enjoy Appendix

Recognizing Plant Species

The project will provide an in-depth discussion on how to build a custom TensorFlow Lite model that is able to perform recognition of plant species from images. The model will run on mobile devices and will be primarily used to recognize different plant species. The model uses a deep convolutional neural network (CNN) for image processing developed on the Keras API of TensorFlow. This chapter also introduces you to the usage of cloud-based APIs for performing image processing. The Cloud Vision API provided by Google Cloud Platform (GCP) has been taken as an example. 

By the end of this chapter, you'll understand the importance of cloud-based services for deep learning (DL) applications as well as the benefits of on-device models for performing offline and instantaneous deep learning tasks on mobile devices.

In this chapter, we will cover the...

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