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Swin Tiny Patch4 Window7 224 Plant Doctor
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Swin Tiny Patch4 Window7 224 Plant Doctor

Developed by plantdoctor
This is a micro image classification model based on the Swin Transformer architecture, specifically fine-tuned for plant health diagnosis tasks, achieving 99.83% accuracy on the evaluation set.
Image Classification
Transformers
Open Source License:Apache-2.0#Plant Disease Identification#High-precision Classification#Agricultural Image Analysis
Downloads 14
Release Time : 4/20/2022

Model Overview

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an image folder dataset, primarily used for image classification tasks related to plant health status.

Model Features

High-precision Plant Health Diagnosis
Achieved a high accuracy rate of 99.83% on the evaluation set, reliably identifying plant health conditions.
Based on Swin Transformer Architecture
Utilizes an advanced vision Transformer architecture with powerful feature extraction capabilities.
Lightweight Model
Uses the tiny variant to reduce computational resource requirements while maintaining performance.

Model Capabilities

Plant Health Status Recognition
Image Classification
Plant Disease Detection

Use Cases

Agricultural Technology
Automatic Plant Disease Diagnosis
Automatically identifies the presence of diseases by taking photos of plant leaves.
Accuracy as high as 99.83%
Farm Health Monitoring
Large-scale monitoring of crop health conditions to promptly detect disease issues.
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