Estimation of Tiller Number in Rice Using a Field Robot and Deep Learning-Reference-Cited by-同舟云学术

Estimation of Tiller Number in Rice Using a Field Robot and Deep Learning

Published:2022 Issue:2 Volume:15 Page:47-60
ISSN:1881-8366
Container-title:Engineering in Agriculture, Environment and Food
language:en
Short-container-title:Engineering in Agriculture, Environment and Food

Author:

SINGH Dhirendranath¹,MORI Tomohiro¹,ICHIURA Shigeru¹,NGUYEN Thanh Tung²,SASAKI Yuka²,KATAHIRA Mitsuhiko²

Affiliation:

1. Department of Agricultural and Environmental Engineering, Biotic Environmental Science, The United Graduate School of Agriculture Sciences, Iwate University

2. Department of Food, Life and Environment, Faculty of Agriculture, Yamagata University

Publisher

Asian Agricultural and Biological Engineering Association

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,Food Science

Link

https://www.jstage.jst.go.jp/article/eaef/15/2/15_47/_pdf

Reference30 articles.

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4. Casado-García, Á., C. Domínguez, M. García-Domínguez, J. Heras, A. Inés, E. Mata and V. Pascual. 2019. CLoDSA: A tool for augmentation in classification, localization, detection, semantic segmentation and instance segmentation tasks. BMC Bio-informatics. 20: 323. https://doi.org/10.1186/s12859-019-2931-1, (Accessed 28 Jun. 2020).

5. Constantino, K. P., E. J. Gonzales, L. M. Lazaro, E. C. Serrano and B. P. Samson. 2018. Towards an automated plant height measurement and tiller segmentation of rice crops using image processing. Mechatronics and Machine Vision in Practice 3, ed. J. Billingsley and P. Brett. 155–168. Switzerland: Springer International Publishing AG. https://doi.org/10.1007/978-3-319-76947-9_11, (Accessed 28 Jun. 2020).

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