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Pond Image Classification 9
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Pond Image Classification 9

Developed by SummerChiam
This is an image classification model built on PyTorch and HuggingPics, specifically designed for pond scene classification.
Image Classification
Transformers
#Pond Water Quality Monitoring#High-Precision Image Classification#Multi-Scenario Adaptability
Downloads 28
Release Time : 7/29/2022

Model Overview

The model can classify various states in pond scenes, including algae, boiling, nighttime boiling, normal, cement normal, nighttime normal, and rainy normal, among others.

Model Features

High Accuracy
Achieved an accuracy of 99.74% on the test set, demonstrating excellent performance.
Multi-Scenario Classification
Capable of identifying various states of ponds under different environmental conditions.
Easy to Use
Automatically generated via HuggingPics tools, making deployment and usage straightforward.

Model Capabilities

Pond scene image classification
Multi-category recognition
Environmental state detection

Use Cases

Environmental Monitoring
Pond Water Quality Monitoring
Assesses water quality by identifying algae growth in ponds through image recognition.
Accurately identifies algae states
Environmental Change Detection
Monitors state changes of ponds under varying weather and time conditions.
Distinguishes between day/night, sunny/rainy scenarios, etc.
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