README.md

IEEE-Project-Agribot

This IEEE project involves development of a chat-bot for agriculture which can assist farmers. Initial phase involves:

• Web app development
• Disease detection in crops
• Weed detection in crops

Resources

• Google Doc Link :- Leaf Detection IEEE

• Web app link :- Web App

• Expected outcome video :- Camera

  This docs file has the links to the datasets found for leaf detection. It also contains details about different leaf diseases.

Project-UI

Github Link

Table of Models

Sr. No.	Code	Link to Model summary	Learning rate	Epochs	Accuracy (Train)	Accuracy (Validation)
1	Model 1 code	Model 1	0.01%	1	8.44 %	8.4375 %
2.0	Model 2_0 code	Model 2_0	0.01%	5	85.69 %	92.13 %
2.1	Model 2_1 code	Model 2_1	0.01%	5	87.20 %	92.40 %
2.2	Model 2_2 code	Model 2_1	0.1%	5	88.52 %	92.91 %

Research Papers for reference

• Integrated IP Approach

• Plant Disease Classifiaction using CNN and Generative Adversial Networks

• Going Deeper with Convolutions

  This might help to learn about CNN's mentioned in the previous paper i.e. Plant Disease Classification using CNN

• Object Detection and Bounding boxes

• Stanford Research Paper for Plant Disease Detection

• Plant Leaf Disease Detection and Classification Using Image Processing Techniques

Code References

• Tensorflow: Load Data
• mc.ai implementation

What's next?

• Linking the model to the web application to dynamically upload images and test for disease
• Improving the model for better accuracy