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R Deep Learning Projects

You're reading from R Deep Learning Projects Master the techniques to design and develop neural network models in R

Product type Paperback

Published in Feb 2018

Publisher Packt

ISBN-13 9781788478403

Length 258 pages

Edition 1st Edition

Languages

R

Tools

Keras

Concepts

Deep Learning

Authors (2):

Yuxi (Hayden) Liu

Pablo Maldonado

View More author details

Table of Contents (7) Chapters

Preface

1. Handwritten Digit Recognition Using Convolutional Neural Networks

2. Traffic Sign Recognition for Intelligent Vehicles FREE CHAPTER

3. Fraud Detection with Autoencoders

4. Text Generation Using Recurrent Neural Networks

5. Sentiment Analysis with Word Embeddings

6. Other Books You May Enjoy

Leave a review - let other readers know what you think

Traffic sign recognition using CNN

As always, we begin by exploring the German Traffic Sign Recognition Benchmark (GTSRB) dataset at http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset.

Getting started with exploring GTSRB

The GTSRB dataset, compiled and generously published by the real-time computer vision research group in Institut für Neuroinformatik, was originally used for a competition of classifying single images of traffic signs. It consists of a training set of 39,209 labeled images and a testing test of 12,630 unlabeled images. The training dataset contains 43 classes—43 types of traffic signs. We will go through all classes and exhibit several samples for each class.

The dataset can...

You have been reading a chapter from

R Deep Learning Projects

Published in: Feb 2018

Publisher: Packt

ISBN-13: 9781788478403

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