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Swin Tiny Patch4 Window7 224 Finetuned Eurosat

Developed by Annabelleabbott
This model is a fine-tuned version based on the Swin Transformer architecture, specifically designed for image classification tasks, achieving 97.26% accuracy on the EuroSAT dataset.
Downloads 14
Release Time : 5/25/2022

Model Overview

This is a fine-tuned Swin Transformer model for image classification tasks, particularly suitable for remote sensing image analysis.

Model Features

High accuracy
Achieved 97.26% classification accuracy on the EuroSAT dataset
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with excellent image understanding capabilities
Lightweight model
Tiny version design, suitable for resource-constrained environments

Model Capabilities

Image classification
Remote sensing image analysis
Multi-category image recognition

Use Cases

Remote sensing analysis
Land cover classification
Classify different land types in satellite images
97.26% classification accuracy
Environmental monitoring
Vegetation type identification
Identify different vegetation types in satellite images
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