Name: iprov2 Dataset
License: https://choosealicense.com/licenses/mit/

Images

242 images

Explore Dataset

Here are a few use cases for this project:

Aquaculture Monitoring: iprov2 can be employed in shrimp farms to monitor and manage shrimp populations, ensuring optimal growth and timely harvesting. By accurately assessing the shrimp-to-notshrimp ratio, farmers can optimize feeding strategies, maintain a balanced ecosystem, and plan ahead for business logistics.
Automated Shrimp Sorting: In seafood processing factories, iprov2 can be used for automated sorting of shrimp from other by-catch or unwanted marine species. This enables faster, more efficient processing and ensures a higher-quality product with reduced contamination risks.
Environmental Impact Studies: Researchers can use iprov2 to analyze images collected from underwater cameras or drones, assessing the distribution of shrimp populations in specific regions. This information can help identify the impact of human activities, such as pollution or overfishing, on shrimp habitats and form strategies for more sustainable practices.
Shrimp Market Quality Control: iprov2 can be used by seafood wholesalers and retailers to quickly and accurately assess the quality of incoming stock. By identifying notshrimp items mixed with the intended shrimps, businesses can ensure the highest standard in their products, helping to protect their brand reputation and maintain customer trust.
Educational and Public Outreach: Institutions and organizations involved in environmental protection and education can use iprov2 to create engaging, interactive exhibits or teaching materials, displaying real-world examples of shrimp population identification. This can foster awareness about marine biodiversity and the importance of safeguarding aquatic ecosystems.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            iprov2_dataset,
                            title = { iprov2 Dataset },
                            type = { Open Source Dataset },
                            author = { counter },
                            howpublished = { \url{ https://universe.roboflow.com/counter-w24at/iprov2 } },
                            url = { https://universe.roboflow.com/counter-w24at/iprov2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { oct },
                            note = { visited on 2024-04-29 },
                            }