Tomato Disease Detection
T
Tomato Disease Detection
Developed by surprisedPikachu007
A tomato disease image classification model based on Vision Transformer architecture, achieving 99.18% accuracy on the evaluation set
Downloads 35
Release Time : 3/9/2023
Model Overview
This model is a fine-tuned version of google/vit-base-patch16-224-in21k, specifically designed to identify diseases in tomato plants, helping farmers quickly diagnose crop health conditions
Model Features
High-precision disease identification
Achieves 99.18% classification accuracy on the test set, reliably identifying various tomato diseases
Based on Vision Transformer
Utilizes advanced ViT architecture with self-attention mechanisms to capture global image features
Lightweight fine-tuning
Requires only a small amount of training data on top of the pre-trained model to achieve excellent performance
Model Capabilities
Plant disease identification
Image classification
Agricultural image analysis
Use Cases
Precision agriculture
Field disease monitoring
Real-time detection of disease types through photos of tomato leaves taken with a smartphone
Accurately identifies early disease symptoms
Greenhouse crop management
Automated monitoring of tomato plant health in greenhouses
Reduces manual inspection workload
Featured Recommended AI Models
Š 2025AIbase