MISSION 01 // BIO-CORENOV 2025
Hybrid ViT Model for Crop Diagnosis
Advanced crop disease detection system
Designed a hybrid ViT + CNN + custom MLP architecture that processes images in parallel to detect 38 crop disease classes, achieving 85% training accuracy and 99.5% validation accuracy. Developed an IoT-ready inference pipeline for real-time deployment with sensor integration and filed a patent covering the model architecture and end-to-end diagnostic workflow.
LOADOUT
- Vision Transformers
- CNN
- Custom MLP
- IoT
MISSION STATS
- 99.5%
- Validation accuracy
- 38
- Disease classes
- IoT-ready
- Inference pipeline
- Filed
- Patent
