junction-DataVim
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BacteriaCountModel-IOT
BacteriaCountModel-IOT PublicA FastAPI-based web service for detecting and counting bacteria in microscopy images using a trained YOLOv8 model.
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WaterClarityPrediction
WaterClarityPrediction PublicA machine learning system for predicting water quality based on physicochemical parameters. This project uses various ML algorithms to classify water quality into three categories: Excellent, Good,…
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OrchestrationAPI
OrchestrationAPI PublicA comprehensive REST API for monitoring aquaculture pools and their sensor readings built with Node.js, Express, and Sequelize ORM. This system tracks various water quality parameters and fish acti…
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FishMovement-Speed
FishMovement-Speed PublicA FastAPI-based application for detecting and tracking fish in videos with swimming speed analysis.
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Repositories
- OrchestrationAPI Public
A comprehensive REST API for monitoring aquaculture pools and their sensor readings built with Node.js, Express, and Sequelize ORM. This system tracks various water quality parameters and fish activities across multiple pools.
junction-DataVim/OrchestrationAPI’s past year of commit activity - BacteriaCountModel-IOT Public
A FastAPI-based web service for detecting and counting bacteria in microscopy images using a trained YOLOv8 model.
junction-DataVim/BacteriaCountModel-IOT’s past year of commit activity - Mobile_app Public
junction-DataVim/Mobile_app’s past year of commit activity - Agent-Fish-Farming-Assistant Public
junction-DataVim/Agent-Fish-Farming-Assistant’s past year of commit activity - API_Prediction Public
junction-DataVim/API_Prediction’s past year of commit activity - FishMovement-Speed Public
A FastAPI-based application for detecting and tracking fish in videos with swimming speed analysis.
junction-DataVim/FishMovement-Speed’s past year of commit activity - sensors-prototypes Public
junction-DataVim/sensors-prototypes’s past year of commit activity - WaterClarityPrediction Public
A machine learning system for predicting water quality based on physicochemical parameters. This project uses various ML algorithms to classify water quality into three categories: Excellent, Good, and Poor.
junction-DataVim/WaterClarityPrediction’s past year of commit activity
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