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

Developed by gjuggler
A bird image classification model based on the Swin Transformer architecture, fine-tuned on a bird dataset with an accuracy of 69.19%
Image Classification
Transformers
Open Source License:Apache-2.0#Bird Image Classification#Swin Transformer Fine-tuning#High Accuracy
Downloads 16
Release Time : 3/11/2023

Model Overview

This model is a vision model based on the Swin Transformer architecture, specifically designed for bird image classification tasks. Fine-tuned on a bird dataset, it can recognize different species of birds.

Model Features

High Accuracy
Achieves a classification accuracy of 69.19% on the bird dataset
Swin Transformer Architecture
Utilizes the advanced Swin Transformer architecture with excellent visual feature extraction capabilities
Lightweight Model
Based on the tiny version of Swin Transformer, suitable for resource-constrained environments

Model Capabilities

Bird Image Classification
Visual Feature Extraction

Use Cases

Wildlife Monitoring
Bird Identification System
Used for automatic bird identification in nature reserves or ecological research
69.19% identification accuracy
Educational Applications
Bird Identification App
Helps users identify bird species from photos
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