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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
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