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

Developed by q2-jlbar
This model is a fine-tuned image classification model based on microsoft/swin-tiny-patch4-window7-224, achieving an accuracy of 96.19% on the evaluation dataset.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Remote sensing image recognition#Swin Transformer architecture
Downloads 14
Release Time : 6/1/2022

Model Overview

This is a fine-tuned Swin Transformer image classification model, specifically designed for high-precision image classification tasks.

Model Features

High accuracy
Achieves 96.19% classification accuracy on the evaluation dataset
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with excellent image understanding capabilities
Lightweight model
Uses the tiny version, requiring relatively low computational resources

Model Capabilities

Image classification
Visual feature extraction

Use Cases

Remote sensing image analysis
Land cover classification
Classify different land types in satellite images
96.19% accuracy
General image classification
Object recognition
Identify main object categories in images
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