| 基于深度学习网络的烟叶质量识别 |
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| 引用本文： | 韩东伟,王小明,王新峰.基于深度学习网络的烟叶质量识别[J].安徽农业科学,2018,46(10):185-188. |
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| 作者姓名： | 韩东伟 王小明 王新峰 |
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| 作者单位： | 河南中烟工业有限责任公司许昌卷烟厂,河南许昌,461000;河南中烟工业有限责任公司许昌卷烟厂,河南许昌,461000;河南中烟工业有限责任公司许昌卷烟厂,河南许昌,461000 |
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| 摘 要： | 概述了烟叶质量和熟成度分类的主要依据,采用自动编码器预训练方法重构的卷积神经网络构建了烟叶质量识别模型,并采用实地采集的数据集进行了实验验证,结果表明重构的深度训练自编码器在分类性能上达到99.92%的准确度。
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| 关 键 词： | 深度学习 智能识别 烟叶质量识别 |
Identification of Tobacco Quality Based on Deep Learning Network |
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| HAN Dong-wei,WANG Xiao-ming,WANG Xin-feng.Identification of Tobacco Quality Based on Deep Learning Network[J].Journal of Anhui Agricultural Sciences,2018,46(10):185-188. |
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| Authors: | HAN Dong-wei WANG Xiao-ming WANG Xin-feng |
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| Abstract: | The main basis for the identification of tobacco leaf quality and ripening degree was summarized.The convolution neural network reconstructed by the automatic encoder pre-training method was used to construct the tobacco leaf quality identification model.The experimental data were used to verify the experimental results and the results showed that the reconstructed depth training self-encoder achieved 99.92％ accuracy in classification performance. |
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