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Vit Base Patch16 224 In21k Eurosat

Developed by philschmid
A high-precision remote sensing image classification model fine-tuned on the EuroSAT dataset based on Google's Vision Transformer architecture
Downloads 28
Release Time : 3/2/2022

Model Overview

This model is an image classification model based on the Vision Transformer (ViT) architecture, specifically fine-tuned for the EuroSAT remote sensing image dataset, achieving a classification accuracy of up to 99.06%.

Model Features

High-precision classification
Achieves 99.06% accuracy and 100% top-3 accuracy on the EuroSAT test set
Based on ViT architecture
Utilizes the Vision Transformer architecture with powerful image feature extraction capabilities
Efficient training
Requires only 5 training epochs to achieve near-perfect classification performance

Model Capabilities

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

Use Cases

Remote sensing analysis
Land use classification
Classify and identify different land types in satellite images
Can accurately identify 10 different land types
Environmental monitoring
Monitor changes in environmental elements such as forests, farmlands, and water bodies
Geographic information systems
Automated map annotation
Automatically identify and annotate geographic features in satellite images
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