WEKO3
アイテム
Feature Reuse Residual Networks for Insect Pest Recognition
https://tokushima-u.repo.nii.ac.jp/records/2008084
https://tokushima-u.repo.nii.ac.jp/records/20080842873994d-388c-44df-8d1c-d3820ad3b0a5
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
access_7_122758.pdf (6.84 MB)
|
.png)
|
| Item type | 文献 / Documents(1) | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 公開日 | 2021-02-08 | |||||||||||||||
| アクセス権 | ||||||||||||||||
| アクセス権 | open access | |||||||||||||||
| 資源タイプ | ||||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||||
| 資源タイプ | journal article | |||||||||||||||
| 出版社版DOI | ||||||||||||||||
| 識別子タイプ | DOI | |||||||||||||||
| 関連識別子 | https://doi.org/10.1109/ACCESS.2019.2938194 | |||||||||||||||
| 言語 | ja | |||||||||||||||
| 関連名称 | 10.1109/ACCESS.2019.2938194 | |||||||||||||||
| 出版タイプ | ||||||||||||||||
| 出版タイプ | VoR | |||||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||||
| タイトル | ||||||||||||||||
| タイトル | Feature Reuse Residual Networks for Insect Pest Recognition | |||||||||||||||
| 言語 | en | |||||||||||||||
| タイトル別表記 | ||||||||||||||||
| その他のタイトル | FR-ResNet s for Insect Pest Recognition | |||||||||||||||
| 言語 | en | |||||||||||||||
| 著者 |
任, 福継
× 任, 福継
WEKO
401
× Liu, Wenjie
× Wu, Guoqing
|
|||||||||||||||
| 抄録 | ||||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||||
| 内容記述 | Insect pests are one of the main threats to the commercially important crops. An effective insect pest recognition method can avoid economic losses. In this paper, we proposed a new and simple structure based on the original residual block and named as feature reuse residual block which combines feature from the input signal of a residual block with the residual signal. In each feature reuse residual block, it enhances the capacity of representation by learning half and reuse half feature. By stacking the feature reuse residual block, we obtained the feature reuse residual network (FR-ResNet) and evaluated the performance on IP102 benchmark dataset. The experimental results showed that FR-ResNet can achieve significant performance improvement in terms of insect pest classification. Moreover, to demonstrate the adaptive of our approach, we applied it to various kinds of residual networks, including ResNet, Pre-ResNet, and WRN, and we tested the performance on a series of benchmark datasets: CIFAR-10, CIFAR-100, and SVHN. The experimental results showed that the performance can be improved obviously than original networks. Based on these experiments on CIFAR-10, CIFAR-100, SVHN, and IP102 benchmark datasets, it demonstrates the effectiveness of our approach. | |||||||||||||||
| 言語 | en | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | Insect pest recognition | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | feature reuse | |||||||||||||||
| キーワード | ||||||||||||||||
| 言語 | en | |||||||||||||||
| 主題Scheme | Other | |||||||||||||||
| 主題 | residual network | |||||||||||||||
| 書誌情報 |
en : IEEE Access 巻 7, p. 122758-122768, 発行日 2019-08-29 |
|||||||||||||||
| 収録物ID | ||||||||||||||||
| 収録物識別子タイプ | ISSN | |||||||||||||||
| 収録物識別子 | 21693536 | |||||||||||||||
| 出版者 | ||||||||||||||||
| 出版者 | IEEE | |||||||||||||||
| 言語 | en | |||||||||||||||
| 権利情報 | ||||||||||||||||
| 言語 | en | |||||||||||||||
| 権利情報 | This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see http://creativecommons.org/licenses/by/4.0/ | |||||||||||||||
| EID | ||||||||||||||||
| 識別子 | 363223 | |||||||||||||||
| 識別子タイプ | URI | |||||||||||||||
| 言語 | ||||||||||||||||
| 言語 | eng | |||||||||||||||
