首页> 外文会议>International Conference on Computer Engineering, Network, and Intelligent Multimedia >A Novel Herbal Leaf Identification and Authentication Using Deep Learning Neural Network
【24h】

A Novel Herbal Leaf Identification and Authentication Using Deep Learning Neural Network

机译:利用深度学习神经网络的新型草药叶识别和认证

获取原文

摘要

Herbal plants are plants that can be used as an alternative to the natural healing of diseases. The existence of herbal plants is still not widely known by the public. It is due to many types of medicinal plants so it requires special knowledge to recognize them. A smart and accurate herbal leaf recognition system is needed to overcome this. This study aims to identify and authenticate herbal leaves using the convolutional neural network and Long Short-Term Memory (CNN-LSTM) methods. Identification was carried out on nine types of herbal leaves divided into two-thirds of training data and one-third of testing data. The results of the identification process were validated by other data not included in training data and testing data, as well as leaf data other than the nine types of leaves identified. The CNN-LSTM method shows good results in the identification process, with an accuracy of 94.96%.
机译:草药植物是植物,可以用作疾病的自然愈合的替代品。草药植物的存在仍然不广为人知。它是由于许多类型的药用植物,所以它需要特殊的知识来识别它们。需要一种智能和准确的草药叶识别系统来克服这一点。本研究旨在使用卷积神经网络和长短期记忆(CNN-LSTM)方法识别和验证草药叶子。识别九种草药叶片分为培训数据的三分之二和三分之一的测试数据。识别过程的结果由不包括在训练数据和测试数据中的其他数据进行验证,以及所识别的九种叶片以外的叶数据。 CNN-LSTM方法在识别过程中显示出良好的结果,精度为94.96%。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号