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Vit Base Patch16 224 Finetuned Eurosat
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Vit Base Patch16 224 Finetuned Eurosat

Developed by Weili
Vision Transformer model based on ViT architecture, achieving 98.89% accuracy after fine-tuning on image classification tasks
Image Classification
Transformers
Open Source License:Apache-2.0#High-precision image classification#ViT fine-tuned model#Remote sensing image recognition
Downloads 32
Release Time : 12/7/2022

Model Overview

This model is an image classification model fine-tuned from Google's ViT-base-patch16-224 pre-trained model on an image folder dataset. Primarily used for high-precision image classification tasks.

Model Features

High accuracy
Achieves 98.89% classification accuracy on the evaluation set
Based on ViT architecture
Utilizes Vision Transformer architecture with powerful image feature extraction capabilities
Efficient fine-tuning
Requires only 3 training epochs to achieve high performance

Model Capabilities

Image classification
Visual feature extraction

Use Cases

Remote sensing image analysis
Land cover classification
Classify land cover types in satellite images
Accuracy can reach 98.89%
General image classification
Object recognition
Identify main object categories in images
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