Paper Abstract and Keywords |
Presentation |
2019-09-23 13:45
Building Datasets Using k-means Clustering and its Evaluation of Training Accuracy by Convolutional Neural Networks Yuichi Miyata, Yoko Uwate, Yoshifumi Nishio (Tokushima Univ.) NLP2019-43 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, aerial photography became easier than before by using the camera loaded in the drone. Also, convolutional neural network (CNN) is one of deep learning and is a network often used for image recognition. With the development of CNN, drones are being researched for applications in various fields such as agriculture. However, the drone camera’s battery and memory are limited. It is important to use the collected data effectively. In this study, we used clustering to make more efficient data sets from the collected image data. This time, we used k-means method to classify the image into two clusters and constructed data sets. This data set is trained using CNN. We examine differences in learning accuracy and computational cost on the data set before and after clustering. We compare the differences in learning accuracy and computational cost with the data set before and after clustering. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Neural Networks / Image Classification / Clustering / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 209, NLP2019-43, pp. 41-44, Sept. 2019. |
Paper # |
NLP2019-43 |
Date of Issue |
2019-09-16 (NLP) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NLP2019-43 |
Conference Information |
Committee |
NLP |
Conference Date |
2019-09-23 - 2019-09-24 |
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(See Japanese page) |
Place (in English) |
Eikokuji Campus, University of Kochi |
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Paper Information |
Registration To |
NLP |
Conference Code |
2019-09-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Building Datasets Using k-means Clustering and its Evaluation of Training Accuracy by Convolutional Neural Networks |
Sub Title (in English) |
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Neural Networks |
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Image Classification |
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Clustering |
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1st Author's Name |
Yuichi Miyata |
1st Author's Affiliation |
Tokushima University (Tokushima Univ.) |
2nd Author's Name |
Yoko Uwate |
2nd Author's Affiliation |
Tokushima University (Tokushima Univ.) |
3rd Author's Name |
Yoshifumi Nishio |
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Tokushima University (Tokushima Univ.) |
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Speaker |
Author-1 |
Date Time |
2019-09-23 13:45:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
NLP2019-43 |
Volume (vol) |
vol.119 |
Number (no) |
no.209 |
Page |
pp.41-44 |
#Pages |
4 |
Date of Issue |
2019-09-16 (NLP) |
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