Fish_P2 Computer Vision Project
Updated a year ago
Here are a few use cases for this project:
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Fish Species Identification: "Fish_P2" can be used by marine biologists and researchers to identify and classify fish species in a specific environment based on the classes G (Good) and NG (Not Good). This can be helpful for biodiversity studies and conservation efforts.
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Fishing Industry: The model can be used to automate the process of sorting through the catch on fishing vessels. By identifying and categorizing fish as G (Good) and NG (Not Good), it can enhance the efficiency of fishing operations and ensure only high-quality fish are processed.
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Aquarium Management: Aquariums can use the model to monitor the health and species of fish in their tanks. The G class can show healthy fish, while NG class can highlight those that may need medical attention or are unfit for showcasing.
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Pollution Impact Research: Environmental researchers can utilize "Fish_P2" to measure the impact of pollution or climate change effects on marine life. By identifying G and NG fishes, the model can help quantify the impact on different species.
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Aquaculture Industry: The aquafarming industry can incorporate "Fish_P2" into monitoring systems to track fish health and growth, identifying G (Good) or NG (Not Good) fish as indicators of overall farm health and efficiency.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
fish_p2_dataset,
title = { Fish_P2 Dataset },
type = { Open Source Dataset },
author = { Test Project 2nd },
howpublished = { \url{ https://universe.roboflow.com/test-project-2nd/fish_p2 } },
url = { https://universe.roboflow.com/test-project-2nd/fish_p2 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { sep },
note = { visited on 2025-01-03 },
}