Paper Abstract and Keywords |
Presentation |
2022-09-14 11:00
Disease and severity classification of coffee leaf images by global low-level feature aggregation network Takuhiro Okada, Satoshi Iizuka, Kazuhiro Fukui (Univ. of Tsukuba) PRMU2022-14 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Coffee leaf disease is one of the most important problems in coffee production. It is very important in the coffee production process to estimate the health condition from the appearance. Using a dataset containing images of a total of six classes, including severity, we conducted a comprehensive experiment to determine how accurately a recent deep learning-based image recognition model can classify the severity of coffee leaf images. Furthermore, based on the results, we constructed a model that can effectively recognize the color distribution of the entire leaf, which is important for disease recognition of coffee leaves, and confirmed that the disease classification can be performed with higher accuracy than the conventional method. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Deep Learning / Image Classification / Imbalanced Data / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 181, PRMU2022-14, pp. 25-30, Sept. 2022. |
Paper # |
PRMU2022-14 |
Date of Issue |
2022-09-07 (PRMU) |
ISSN |
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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PRMU2022-14 |
Conference Information |
Committee |
PRMU |
Conference Date |
2022-09-14 - 2022-09-15 |
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(See Japanese page) |
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(See Japanese page) |
Topics (in English) |
Deep generative model |
Paper Information |
Registration To |
PRMU |
Conference Code |
2022-09-PRMU |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Disease and severity classification of coffee leaf images by global low-level feature aggregation network |
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Deep Learning |
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Image Classification |
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Imbalanced Data |
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1st Author's Name |
Takuhiro Okada |
1st Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
2nd Author's Name |
Satoshi Iizuka |
2nd Author's Affiliation |
University of Tsukuba (Univ. of Tsukuba) |
3rd Author's Name |
Kazuhiro Fukui |
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University of Tsukuba (Univ. of Tsukuba) |
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Speaker |
Author-1 |
Date Time |
2022-09-14 11:00:00 |
Presentation Time |
15 minutes |
Registration for |
PRMU |
Paper # |
PRMU2022-14 |
Volume (vol) |
vol.122 |
Number (no) |
no.181 |
Page |
pp.25-30 |
#Pages |
6 |
Date of Issue |
2022-09-07 (PRMU) |
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