Noninvasive Diagnosis of Seedless Fruit Using Deep Learning in Persimmon-Reference-Cited by-同舟云学术

Noninvasive Diagnosis of Seedless Fruit Using Deep Learning in Persimmon

Published:2021 Issue:2 Volume:90 Page:172-180
ISSN:2189-0102
Container-title:The Horticulture Journal
language:en
Short-container-title:Hortic J

Author:

Masuda Kanae¹,Suzuki Maria¹,Baba Kohei²,Takeshita Kouki²,Suzuki Tetsuya³,Sugiura Mayu³,Niikawa Takeshi³,Uchida Seiichi²,Akagi Takashi¹

Affiliation:

1. Graduate School of Environmental and Life Science, Okayama University

2. Department of Advanced Information Technology, Kyushu University

3. Gifu Prefectural Agricultural Technology Center

Publisher

Japanese Society for Horticultural Science

Subject

Horticulture,Plant Science

Link

https://www.jstage.jst.go.jp/article/hortj/90/2/90_UTD-248/_pdf

Reference36 articles.

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2. Alber, M., S. Lapuschkin, P. Seegerer, M. Hägele, K. T. Schütt, G. Montavon, W. Samek, K. R. Muller, S. Dähne and P. J. Kindermans. 2019. iNNvestigate neural networks!. J. Mach. Learn. Res. 20: 1–8.

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4. Bach, S., A. Binder, G. Montavon, F. Klauschen, K. R. Müller and W. Samek. 2015. On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation. PLoS One. DOI: 10.1371/journal.pone.0130140.

5. Cubero, S., N. Aleixos, E. Moltó, J. Gómez-Sanchis and J. Blasco. 2011. Advances in machine vision applications for automatic inspection and quality evaluation of fruits and vegetables. Food Bioproc. Technol. 4: 487–504.

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