shrimp-object-tracking-and-counting Computer Vision Project
Updated a year ago
110
8
Here are a few use cases for this project:
-
Aquaculture Monitoring: In shrimp farms, this model can be used to classify and count shrimps automatically, allowing farm management to track the growth and health of the shrimps, manage feed levels, and estimate harvest times.
-
Fisheries Sciences Research: Researchers studying shrimps can use this model to automatically identify and quantify different classes of shrimps in captured footage or images, speeding up data collection.
-
Commercial Fishing: The model could provide real-time quantification and categorization of shrimp catch on fishing vessels, enabling an accurate measure of the haul and helping to ensure correct compliance with fishing quota legislation.
-
Quality Assurance in Food Processing: Food processing plants dealing with shrimp can leverage the model to automate quality inspection, which aids in sorting the shrimps based on their sizes or types, improving efficiency and standardization.
-
Environmental Monitoring and Conservation: The model can play a crucial role in monitoring biodiversity in a certain water area by identifying and counting the shrimp population. This information can be used to determine the health of the ecosystem and inform conservation strategies.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
shrimp-object-tracking-and-counting_dataset,
title = { shrimp-object-tracking-and-counting Dataset },
type = { Open Source Dataset },
author = { ESPOL },
howpublished = { \url{ https://universe.roboflow.com/espol-magof/shrimp-object-tracking-and-counting } },
url = { https://universe.roboflow.com/espol-magof/shrimp-object-tracking-and-counting },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { sep },
note = { visited on 2024-11-04 },
}