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Swin Tiny Patch4 Window7 224 Finetuned Eurosat

Developed by nielsr
A fine-tuned image classification model based on the Swin Transformer architecture, achieving 97.44% accuracy on the image folder dataset
Downloads 51
Release Time : 4/12/2022

Model Overview

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 for image classification tasks, excelling in image classification tasks

Model Features

High accuracy
Achieves 97.44% classification accuracy on the evaluation set
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with excellent visual feature extraction capabilities
Lightweight model
Designed with tiny variant, suitable for deployment in resource-constrained environments

Model Capabilities

Image classification
Visual feature extraction

Use Cases

Remote sensing image analysis
Land cover classification
Classify different land types in satellite images
97.44% accuracy
General image classification
Object recognition
Identify main object categories in images
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