AI-Powered Paddy Protection
Revolutionizing rice farming with intelligent disease diagnosis
Where deep learning meets agriculture
Boost your yield with our advanced disease detection system
Innovative solutions for resilient crops
Transforming rice farming with AI-driven disease detection
Protect Your Paddy
Early disease detection for thriving rice fields
Welcome to Paddy Pathologist: Your Partner in Paddy Protection
Discover how technology can revolutionize rice farming. Our mobile app, powered by deep learning, empowers farmers to quickly identify and combat diseases, safeguarding their yields. Explore our research initiatives below and download the app now. Researchers and industry partners can access our valuable datasets to drive innovation in paddy health.
AI-based Rice Leaf Disease Identification Enhanced by Dynamic Mode Decomposition
This project focuses on improving the identification of rice leaf diseases using transfer-learned deep learning models. By integrating a Dynamic Mode Decomposition (DMD) approach with attention-driven preprocessing, the project enhances model accuracy, achieving up to 100% in testing and 94.33% in on-field scenarios. The DMD preprocessing technique significantly improves the model's ability to focus on diseased areas, leading to better performance in disease identification.
Improved Bacterial Leaf Blight Severity Progression Analysis in Rice Using Enhanced Segmentation and Deep Learning
We present a novel approach to analyze Bacterial Leaf Blight (BLB) in rice, a severe threat to production. A dataset of 6,656 rice leaf images was collected and categorized into five severity stages. We evaluated five pre-trained CNN models and applied unsupervised segmentation techniques. Detectron2, paired with MobileNet-v2, achieved 94.07% accuracy in classifying disease stages. The custom dataset will be available for further research in agricultural disease management.