WEKO3
アイテム
Grading Fruits and Vegetables Using RGB-D Images and Convolutional Neural Network
http://hdl.handle.net/10228/00006888
http://hdl.handle.net/10228/0000688892a1e580-bab9-4a0c-bddb-0f438659f663
| 名前 / ファイル | ライセンス | アクション |
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ssci17rgbd.pdf (793.3 kB)
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| アイテムタイプ | 会議発表論文 = Conference Paper(1) | |||||||||||
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| 公開日 | 2018-08-24 | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_5794 | |||||||||||
| 資源タイプ | conference paper | |||||||||||
| タイトル | ||||||||||||
| タイトル | Grading Fruits and Vegetables Using RGB-D Images and Convolutional Neural Network | |||||||||||
| 言語 | en | |||||||||||
| 言語 | ||||||||||||
| 言語 | eng | |||||||||||
| 著者 |
Nishi, Toshiki
× Nishi, Toshiki× 黒木, 秀一× 松尾, 一矢
WEKO
15851
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| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | This paper presents a method for grading fruits and vegetables by means of using RGB-D (RGB and depth) images and convolutional neural network (CNN). Here, we focus on grading according to the size of objects. First, the method transforms positions of pixels in RGB image so that the center of the object in 3D space is placed at the position equidistant from the focal point by means of using the corresponding depth image. Then, with the transformed RGB images involving equidistant objects, the method uses CNN for learning to classify the objects or fruits and vegetables in the images for grading according to the size, where the CNN is structured for achieving both size sensitivity for grading and shift invariance for reducing position error involved in images. By means of numerical experiments, we show the effectiveness and the analysis of the present method. | |||||||||||
| 備考 | ||||||||||||
| 内容記述タイプ | Other | |||||||||||
| 内容記述 | The 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), November 27 to December 1, 2017, Honolulu, Hawaii, USA | |||||||||||
| 書誌情報 |
2017 IEEE Symposium Series on Computational Intelligence (SSCI) 発行日 2017-12-01 |
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| 出版社 | ||||||||||||
| 出版社 | IEEE | |||||||||||
| DOI | ||||||||||||
| 関連タイプ | isVersionOf | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.1109/SSCI.2017.8285278 | |||||||||||
| ISBN | ||||||||||||
| 識別子タイプ | ISBN | |||||||||||
| 関連識別子 | 978-1-5386-2726-6 | |||||||||||
| ISBN | ||||||||||||
| 識別子タイプ | ISBN | |||||||||||
| 関連識別子 | 978-1-5386-2727-3 | |||||||||||
| 著作権関連情報 | ||||||||||||
| 権利情報 | Copyright (c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | grading fruits and vegetables according to size | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | RGB-D images | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | convolutional neural network | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | size sensitivity | |||||||||||
| キーワード | ||||||||||||
| 主題Scheme | Other | |||||||||||
| 主題 | shift invariance | |||||||||||
| 出版タイプ | ||||||||||||
| 出版タイプ | AM | |||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||||||||
| 査読の有無 | ||||||||||||
| 値 | yes | |||||||||||
| 研究者情報 | ||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/12_ja.html | |||||||||||
| 論文ID（連携） | ||||||||||||
| 値 | 10324510 | |||||||||||
| 連携ID | ||||||||||||
| 値 | 7182 | |||||||||||
