Current Project
Wheat Rust Disease Classification System
A convolutional neural network model for accurate classification of wheat rust diseases from leaf images.
Status
Completed
Sector
AI & Agriculture
Stack
07
Project Overview
This system leverages CNN architectures to classify wheat rust diseases, improving diagnosis accuracy and agricultural productivity.
Tech Stack
Challenge
Wheat rust diseases are difficult to distinguish manually due to visual similarity.
Delivery
A high-accuracy CNN model with optimized preprocessing and evaluation metrics.
Impact
⭐⭐⭐⭐⭐ Improved disease classification accuracy Reduced dependency on manual inspection Scalable AI-based agricultural solution
Project Highlights
Highlight 01
Multi-class disease classification
Highlight 02
Data augmentation techniques
Highlight 03
Model evaluation and tuning
Highlight 04
REST API deployment
Highlight 05
Scalable inference system
Next Project
Continue with Mango Leaf Disease Detection System.
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