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Convnext Tiny 224 Finetuned Eurosat Albumentations
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Convnext Tiny 224 Finetuned Eurosat Albumentations

Developed by jypasona
This model is a fine-tuned image classification model based on the ConvNeXt-Tiny architecture, trained on the EuroSAT dataset with albumentations for data augmentation, achieving 98.48% accuracy on the evaluation set.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision Image Classification#Satellite Image Recognition#ConvNeXt Architecture
Downloads 18
Release Time : 12/27/2022

Model Overview

This is a fine-tuned model for image classification, based on Facebook's ConvNeXt-Tiny architecture, trained on the EuroSAT dataset, suitable for remote sensing image classification tasks.

Model Features

High Accuracy
Achieves 98.48% classification accuracy on the EuroSAT evaluation set.
Data Augmentation
Uses albumentations for data augmentation to improve model generalization.
Lightweight Architecture
Based on the ConvNeXt-Tiny architecture, reducing computational resource requirements while maintaining performance.

Model Capabilities

Image Classification
Remote Sensing Image Analysis
Multi-class Recognition

Use Cases

Remote Sensing Analysis
Land Use Classification
Classify land use types in satellite images.
Can accurately identify 10 different land use types.
Environmental Monitoring
Monitor changes in land cover.
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