ConvNeXt-Tiny-224 Finetuned Eurosat Albumentations Open-Source Image Classification Model - High-Precision Image Category Recognition

Convnext Tiny 224 Finetuned Eurosat Albumentations

Developed by toshio19910306

A fine-tuned image classification model based on ConvNeXt-Tiny architecture, achieving 98.15% accuracy on the EuroSAT dataset

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Release Time : 12/27/2022

Model Overview

This model is a fine-tuned version of ConvNeXt-Tiny for image classification tasks, particularly suitable for satellite image analysis

High Accuracy

Achieves 98.15% classification accuracy on the EuroSAT dataset

Lightweight Architecture

Based on ConvNeXt-Tiny architecture, suitable for resource-constrained environments

Data Augmentation Optimization

Uses Albumentations for data augmentation to improve model generalization

Satellite Image Classification

Multi-class Image Recognition

High-precision Visual Analysis

Remote Sensing Analysis

Land Use Classification

Classify and identify land types in satellite images

Accurately identifies 10 different land types

Environmental Monitoring

Monitor environmental indicators such as forest cover and water body changes

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1452	1.0	190	0.1335	0.97
0.0683	2.0	380	0.0825	0.9763
0.0584	3.0	570	0.0671	0.9815

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