A Robust Mature Tomato Detection in Greenhouse Scenes Using Machine Learning and Color Analysis-Reference-Cited by-同舟云学术

A Robust Mature Tomato Detection in Greenhouse Scenes Using Machine Learning and Color Analysis

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19
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Author:

Liu Guoxu¹,Mao Shuyi²,Jin Hui²,Kim Jae Ho²

Affiliation:

1. Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea and Computer Software Institute, Weifang University of Science & Technology, Shouguang, China

2. Dept. of Electronics Engineering, Pusan National University, Busan, Rep. of Korea

Publisher

ACM Press

Reference14 articles.

1. Zhao, Y., Gong, L., Huang, Y., & Liu, C. 2016. A review of key techniques of vision-based control for harvesting robot. Computers and Electronics in Agriculture, 127 (2016), 311--323.

2. Bulanon, D. M., Kataoka, T., Ota, Y., & Hiroma, T. 2002. AE-automation and emerging technologies: a segmentation algorithm for the automatic recognition of Fuji apples at harvest. Biosystems Engineering, 83, 4 (2002), 405--412.

3. Yin, H., Chai, Y., Yang, S. X., & Mittal, G. S. 2009. Ripe tomato extraction for a harvesting robotic system. In Systems, Man and Cybernetics, 2009. SMC 2009. IEEE International Conference on (San Antonio, Texas, USA, October 11-14, 2009). 2984--2989.

4. Wei, X., Jia, K., Lan, J., Li, Y., Zeng, Y., & Wang, C. 2014. Automatic method of fruit object extraction under complex agricultural background for vision system of fruit picking robot. Optik-International Journal for Light and Electron Optics, 125, 19 (2014), 5684--5689.

5. Krig, Scott. Computer vision metrics. Springer, 2016.

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