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Convnext Tiny Finetuned Eurosat

Developed by mrm8488
This is a ConvNeXT-tiny model fine-tuned on the EuroSAT satellite image dataset for land use classification tasks, achieving an accuracy of 98.05%.
Downloads 25
Release Time : 4/23/2022

Model Overview

This model is a lightweight version based on the ConvNeXT architecture, specifically optimized for satellite image classification tasks, suitable for land use and land cover classification applications.

Model Features

High-precision Satellite Image Classification
Achieves 98.05% classification accuracy on the EuroSAT dataset, suitable for precise land use analysis.
Lightweight Architecture
Based on the ConvNeXT-tiny architecture, it reduces computational resource requirements while maintaining high performance.
Modern Convolutional Design
Adopts a modern convolutional network design inspired by vision Transformers, combining the advantages of CNNs and Transformers.

Model Capabilities

Satellite Image Classification
Land Use Recognition
Land Cover Classification

Use Cases

Geographic Information Systems
Land Use Monitoring
Automatically identifies and classifies different land use types in satellite images.
98.05% accuracy
Environmental Change Detection
Detects land use changes through time-series analysis.
Agricultural Applications
Farmland Identification
Identifies farmland areas from satellite images.
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