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Global Descriptors of Convolution Neural Networks for Remote Scene Images Classification Read chapter Read first chapter

2020 | OriginalPaper | Chapter

A Guideline for Object Detection Using Convolutional Neural Networks

Authors : Xingguo Zhang, Guoyue Chen, Kazuki Saruta, Yuki Terata

Published in: Artificial Intelligence in China

Publisher: Springer Singapore

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Abstract

The main purpose of object detection is to detect and locate specific targets from images. The traditional detection methods are usually complex and require prior knowledge of the detection target. In this paper, we will introduce how to use convolutional neural networks to perform object detection from image. This is one of the important areas of computer vision. In order to build up to object detection, we first learn about how we can get the object localization or landmark by a neural network. And then I will give the detail of sliding windows detection algorithm and introduce how to use the convolutional implementation of sliding windows to speed up the process. Then we will introduce the transfer learning and how to prepare your own learning data for training networks.

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Metadata
Title
A Guideline for Object Detection Using Convolutional Neural Networks
Authors
Xingguo Zhang
Guoyue Chen
Kazuki Saruta
Yuki Terata
Copyright Year
2020
Publisher
Springer Singapore
Book
Artificial Intelligence in China

Print ISBN: 978-981-15-0186-9

Electronic ISBN: 978-981-15-0187-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-0187-6_18