Swin Tiny Patch4 Window7 224 Finetuned Eurosat
A fine-tuned image classification model based on the Swin Transformer architecture, achieving 97.44% accuracy on the image folder dataset
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Release Time : 4/12/2022
Model Overview
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 for image classification tasks, excelling in image classification tasks
Model Features
High accuracy
Achieves 97.44% classification accuracy on the evaluation set
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with excellent visual feature extraction capabilities
Lightweight model
Designed with tiny variant, suitable for deployment in resource-constrained environments
Model Capabilities
Image classification
Visual feature extraction
Use Cases
Remote sensing image analysis
Land cover classification
Classify different land types in satellite images
97.44% accuracy
General image classification
Object recognition
Identify main object categories in images
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