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You're reading from Java Deep Learning Projects Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Product type Paperback

Published in Jun 2018

Publisher Packt

ISBN-13 9781788997454

Length 436 pages

Edition 1st Edition

Languages

Java

Tools

Deeplearning4j

Concepts

Deep Learning

Table of Contents (17) Chapters

Title Page

Packt Upsell

Contributors

Preface

1. Getting Started with Deep Learning FREE CHAPTER

2. Cancer Types Prediction Using Recurrent Type Networks

3. Multi-Label Image Classification Using Convolutional Neural Networks

4. Sentiment Analysis Using Word2Vec and LSTM Network

5. Transfer Learning for Image Classification

6. Real-Time Object Detection using YOLO, JavaCV, and DL4J

7. Stock Price Prediction Using LSTM Network

8. Distributed Deep Learning – Video Classification Using Convolutional LSTM Networks

9. Playing GridWorld Game Using Deep Reinforcement Learning

10. Developing Movie Recommendation Systems Using Factorization Machines

11. Discussion, Current Trends, and Outlook

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Index

Object detection from images and videos

Deep learning has been widely applied to various computer vision tasks such as image classification, object detection, semantic segmentation, and human pose estimation. When we intend to solve the object detection problem from images, the whole process starts from object classification. Then we perform object localization and finally, we perform the object detection.

Note

This project is highly inspired by the Java Autonomous driving – Car detection article by Klevis Ramo (http://ramok.tech/). Also, some theoretical concepts are used (but significantly extended for this need) with due permission from the author.

Object classification, localization, and detection

In an object classification problem, from a given image (or video clip), we're interested to know if it contains a region of interest (ROI) or object. More formally, "the image contains a car" versus "the image does not contain any car." To solve this problem, over the last few years, ImageNet...