DeepAI AI Chat
Log In Sign Up

Image Recognition of Tea Leaf Diseases Based on Convolutional Neural Network

by   Xiaoxiao Sun, et al.

In order to identify and prevent tea leaf diseases effectively, convolution neural network (CNN) was used to realize the image recognition of tea disease leaves. Firstly, image segmentation and data enhancement are used to preprocess the images, and then these images were input into the network for training. Secondly, to reach a higher recognition accuracy of CNN, the learning rate and iteration numbers were adjusted frequently and the dropout was added properly in the case of over-fitting. Finally, the experimental results show that the recognition accuracy of CNN is 93.75 network is 89.36 based on CNN is better in classification and can improve the recognition efficiency of tea leaf diseases effectively.


page 2

page 3


Identify Apple Leaf Diseases Using Deep Learning Algorithm

Agriculture is an essential industry in the both society and economy of ...

Image Recognition Using Scale Recurrent Neural Networks

Convolutional Neural Network(CNN) has been widely used for image recogni...

Tree Recognition APP of Mount Tai Based on CNN

Mount Tai has abundant sunshine, abundant rainfall and favorable climati...

Text Matching as Image Recognition

Matching two texts is a fundamental problem in many natural language pro...

Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System Images

Studies recently accomplished on the Enteric Nervous System have shown t...

Winograd Convolution for DNNs: Beyond linear polinomials

We investigated a wider range of Winograd family convolution algorithms ...