Application of agricultural pest classification Version==1.1

DEEP learning App using CNN Algorithm to Classify Insect Pests Images

Classification of images of agricultural insect pests targeting strategic crops with 12 different types of insects

Visit APP

UI

Steps:

• Upload an image of an insect pest to classify it
• Wait until the result appears
• The name of the pest and methods to combat it will appear

CNN (Convolutional Neural Network Architecture)

A CNN typically has three layers: a convolutional layer, a pooling layer, and a fully connected layer.

• Convolution Layer

• Pooling Layer

The pooling layer replaces the output of the network at certain locations by deriving a summary statistic of the nearby outputs.

• Fully Connected Layer

Neurons in this layer have full connectivity with all neurons in the preceding and succeeding layer as seen in regular FCNN. This is why it can be computed as usual by a matrix multiplication followed by a bias effect.

packes & framework & algo

• CNN
• Python =3.9
• jupyter notebook =defalut
• numpy
• pandas
• matplotlib
• streamlit
• tensorflow
• keras

streamlit server

CN.PY file

read the nootebook, some of result :

jupyter notebook

References

• ( Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville published by MIT Press, 2016)