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

Developed by aricibo
A fine-tuned image classification model based on Swin Transformer Tiny architecture, achieving 97.26% 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 15
Release Time : 5/20/2022

Model Overview

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 for image classification tasks, specifically designed for remote sensing image classification

Model Features

High Accuracy
Achieves 97.26% classification accuracy on the EuroSAT dataset
Based on Swin Transformer
Utilizes advanced Swin Transformer architecture with powerful feature extraction capabilities
Lightweight Design
Tiny version suitable for deployment in resource-constrained environments

Model Capabilities

Remote sensing image classification
Multi-category image recognition
High-precision scene understanding

Use Cases

Remote Sensing Analysis
Land Use Classification
Identify different land types in satellite images
97.26% accuracy
Environmental Monitoring
Monitor environmental elements such as forest coverage and water body changes
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