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Swin Tiny Patch4 Window7 224 Finetuned Birds
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Swin Tiny Patch4 Window7 224 Finetuned Birds

Developed by gjuggler
A bird image classification model based on Swin Transformer architecture, fine-tuned on bird datasets with an accuracy of 82.15%
Image Classification
Transformers
Open Source License:Apache-2.0#Bird Image Classification#High Accuracy Recognition#Swin Transformer Architecture
Downloads 17
Release Time : 3/11/2023

Model Overview

This model is an image classification model fine-tuned on bird datasets based on microsoft/swin-tiny-patch4-window7-224, specifically designed for recognizing different bird species.

Model Features

High Accuracy
Achieves 82.15% classification accuracy on bird datasets
Based on Swin Transformer
Utilizes the advanced Swin Transformer architecture with excellent visual feature extraction capabilities
Lightweight Model
The tiny version is suitable for deployment in resource-constrained environments

Model Capabilities

Bird Image Classification
Visual Feature Extraction

Use Cases

Wildlife Monitoring
Automatic Bird Recognition
Used for automatic bird recognition and classification in nature reserves or ecological research
Accurately identifies different bird species
Educational Applications
Bird Identification Teaching Tool
Serves as an educational tool to help students identify different bird species
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