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

Developed by nielsr
A fine-tuned image classification model based on the Swin Transformer architecture, achieving 98.3% accuracy on the image folder dataset.
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#Remote sensing image analysis#Swin-Transformer architecture
Downloads 16
Release Time : 8/29/2022

Model Overview

This model is a fine-tuned image classification model based on microsoft/swin-tiny-patch4-window7-224, suitable for general image classification tasks.

Model Features

High accuracy
Achieves 98.3% classification accuracy on the evaluation set
Swin Transformer architecture
Utilizes the advanced Swin Transformer architecture with efficient local attention mechanisms
Fine-tuning optimization
Fine-tuned based on a pre-trained model to adapt to specific classification tasks

Model Capabilities

Image classification
Feature extraction

Use Cases

Remote sensing image analysis
Satellite image classification
Classify remote sensing image datasets such as EuroSAT
Highly accurate land cover classification
General image classification
Object recognition
Identify main objects or scenes in images
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