fish-images Computer Vision Project
Updated 3 years ago
Here are a few use cases for this project:
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Aquatic Research: Research institutions or marine biologists can use the "fish-images" model to identify various fish species in underwater imagery, thus aiding in ecological surveys, biodiversity studies, and in monitoring of fish populations.
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Fishing Industry: The commercial fishing industry can employ the model to distinguish between various fish classes in their catch. This could assist in identifying and separating endangered or non-target species, promoting sustainable fishing practices.
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Aquarium Management: In aquariums, the model can help in recognizing different fish species for inventory control, health assessment, and care protocols. It can contribute to a better understanding of species-specific behaviors.
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Recreational Fishing App: An app can use the model to help recreational fishers identify the kinds of fish they catch. This can also include information about regulations and whether a specific type of fish can be legally kept or needs to be released.
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Environmental Conservation: The model could be integrated with underwater drones or observation platforms to monitor marine ecosystems, helping conservationists detect the presence of invasive species or monitor the recovery of endangered species.
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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-images_dataset,
title = { fish-images Dataset },
type = { Open Source Dataset },
author = { Mikhail Litvinov },
howpublished = { \url{ https://universe.roboflow.com/mikhail-litvinov/fish-images } },
url = { https://universe.roboflow.com/mikhail-litvinov/fish-images },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2021 },
month = { dec },
note = { visited on 2024-11-14 },
}