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Swin Tiny Patch4 Window7 224 Finetuned Eurosat
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Swin Tiny Patch4 Window7 224 Finetuned Eurosat

Developed by Chandanab
A fine-tuned image classification model based on Swin Transformer architecture, achieving 93.94% accuracy on the EuroSAT dataset
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Remote sensing image recognition#Swin Transformer architecture
Downloads 13
Release Time : 8/2/2022

Model Overview

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224, specifically designed for image classification tasks, demonstrating excellent performance on the EuroSAT dataset

Model Features

High accuracy
Achieves 93.94% classification accuracy on the EuroSAT dataset
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with excellent visual feature extraction capabilities
Lightweight model
The tiny version is suitable for deployment in resource-constrained environments

Model Capabilities

Image classification
Remote sensing image analysis
Multi-category recognition

Use Cases

Remote sensing image analysis
Land use classification
Classify different land types in satellite images
93.94% accuracy
Agricultural monitoring
Identify agricultural-related areas such as farmland, forests, and water bodies
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