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Intelligent Mobile Projects with TensorFlow

You're reading from   Intelligent Mobile Projects with TensorFlow Build 10+ Artificial Intelligence apps using TensorFlow Mobile and Lite for iOS, Android, and Raspberry Pi

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788834544
Length 404 pages
Edition 1st Edition
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Author (1):
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Jeff Tang Jeff Tang
Author Profile Icon Jeff Tang
Jeff Tang
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Table of Contents (14) Chapters Close

Preface 1. Getting Started with Mobile TensorFlow FREE CHAPTER 2. Classifying Images with Transfer Learning 3. Detecting Objects and Their Locations 4. Transforming Pictures with Amazing Art Styles 5. Understanding Simple Speech Commands 6. Describing Images in Natural Language 7. Recognizing Drawing with CNN and LSTM 8. Predicting Stock Price with RNN 9. Generating and Enhancing Images with GAN 10. Building an AlphaZero-like Mobile Game App 11. Using TensorFlow Lite and Core ML on Mobile 12. Developing TensorFlow Apps on Raspberry Pi 13. Other Books You May Enjoy

Classifying Images with Transfer Learning

The sample TensorFlow iOS apps, simple and camera, and the Android app TF Classify, described in the previous chapter all use the Inception v1 model, a pretrained image classification deep neural network model made publicly available by Google. The model is trained for ImageNet (http://image-net.org), one of the largest and best-known image databases with over 10 million images annotated for object classes. The Inception model can be used to classify an image into one of the 1,000 classes, listed at http://image-net.org/challenges/LSVRC/2014/browse-synsets. Those 1,000 object classes include quite a few dog breeds, among many kinds of objects. But the accuracy for recognizing dog breeds is not that high, around 70%, because the model is trained for recognizing a large number of objects, instead of a specific set of objects such as dog...

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