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Swin Tiny Patch4 Window7 224 Finetuned Algae Rgb
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Swin Tiny Patch4 Window7 224 Finetuned Algae Rgb

Developed by samitizerxu
A vision model based on Swin Transformer Tiny architecture, specifically fine-tuned for algae RGB image classification tasks
Image Classification
Transformers
Open Source License:Apache-2.0#Algae Image Classification#Swin-Transformer Fine-tuning#RGB Image Recognition
Downloads 18
Release Time : 2/14/2023

Model Overview

This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an algae RGB image dataset, primarily used for algae image classification tasks

Model Features

Efficient Image Classification
Based on Swin Transformer architecture, it maintains high accuracy while having low computational overhead
Algae Recognition Optimization
Specifically fine-tuned for algae RGB images, suitable for environmental monitoring and water quality analysis applications
Balanced Performance
Achieves 61.8% accuracy on the evaluation set, capable of processing 153 samples per second

Model Capabilities

RGB Image Classification
Algae Recognition
Environmental Monitoring Image Analysis

Use Cases

Environmental Monitoring
Water Quality Assessment
Evaluates water quality by analyzing the distribution and types of algae in water bodies
Algal Bloom Early Warning
Detects the presence of harmful algae, providing early warnings for algal bloom outbreaks
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