computer vision
Crop DiseaseAI - Real-time Crop Disease Detection
Developed a deep learning model achieving 89.6% validation accuracy for detecting diseases in soybean and sugarcane crops.
January 1, 20263 technologies
About the Project
Developed a deep learning model using PyTorch EfficientNet-B0 achieving 89.6% validation accuracy for detecting diseases in soybean and sugarcane crops. Built a farmer advisory system providing actionable recommendations.
Key Features
- ✓Responsive design that works on all devices
- ✓Optimized performance with lazy loading
- ✓Accessible and follows WCAG guidelines
- ✓Clean, maintainable codebase
Technologies Used
PyTorchEfficientNet-B0Computer Vision