Simulation modelling of crop diseases using a Susceptible-Exposed-Infectious-Removed (SEIR) model in R

Rice Disease Prediction App using SVM Machine learning algorithm with tkinter

Rice Disease Detection application to detect diseases that often attack rice crops including Brown Spot, Hispa, and Leaf Blast).

In this project, I used Hybrid deep CNN transfer learning on rice plant images, perform classification and identification of various rice diseases. I employed Transfer Learning to generate our deep learning model using Rice Leaf Dataset from a secondary source. The proposed model is 90.8% accurate, Experiments show that the proposed approach is …

The Rice is Right: Early Detection of Rice Leaf Disease using Convolutional Neural Networks

Uses Tensorflow to train a model to detect Rice and Potato plant Diseases

My Bachelor Thesis

Rice leaf disease detection and classification using deep learning algorithms. We used CNN with different flavors.

I developed this portfolio using CNN to train a model to detect Rice and Potato plant Diseases. To see the website visit

Web Application for Rice Disease Image Classification

This dataset contains 120 jpg images of disease-infected rice leaves. The images are grouped into 3 classes based on the type of disease. There are 40 images in each class. Classes 2. Leaf smut 3. Brown spot 3.Bacterial leaf blight

The open source code for the paper "A Hybrid Multi-stage Model based on YOLO and Modified Inception Network for Rice Leaf Disease Analysis" Hybrid_Multi_Stage_DeepLearing_Approach