Application of Pattern Recognition in Sugarcane Seed Cutting Operation

DOI

10.2991/smont-19.2019.57How to use a DOI?

Keywords

deep learning; pattern recognition; sugarcane seed cutting; image acquisition

Abstract

According to the actual needs of sugarcane seed cutting operation and pattern recognition technology, an intelligent sugarcane seed cutting recognition system is constructed based on deep separable convolution neural network. The system can identify sugarcane buds in the sugarcane planting and cutting process, so that they will not be damaged, thus reducing the rate of injured buds and improving the cutting quality. The system has the characteristics of simple structure design and strong practicability. It can effectively solve the problem of visual sorting in sugarcane seed cutting operation. It helps to realize intelligent recognition and accurate cutting, with the recognition rate of 99%.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yang Xiao
AU  - Jing Xu
PY  - 2019/04
DA  - 2019/04
TI  - Application of Pattern Recognition in Sugarcane Seed Cutting Operation
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation, Optimization and Numerical Techniques (SMONT 2019)
PB  - Atlantis Press
SP  - 258
EP  - 261
SN  - 1951-6851
UR  - https://doi.org/10.2991/smont-19.2019.57
DO  - 10.2991/smont-19.2019.57
ID  - Xiao2019/04
ER  -