pakanikan Object Detection Dataset and Pre-Trained Model by pakan

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Explore Dataset

Here are a few use cases for this project:

"Aquaculture Feed Quality Control": Aquaculture businesses can use the pakanikan model to analyze and monitor the quality and variety of fish feed, ensuring optimal diet for fish for better growth and sustainability.
"Pet Store Management": Pet stores can use this model to sort and categorize different types of fish feed, making it easy to manage inventory and ensure correct feed types for different varieties of fish species in the store.
"Fish Breeding Program": Researchers and breeders can employ this model to identify and classify specific types of fish feed desirable for breeding certain types of fish. This could aid in the maintenance of fish health and effective breeding strategies.
"Fish Feed Manufacturing": In the fish feed production industry, this model can be used to classify and identify finished fish feed products accurately, facilitating quality control and assurance before distribution to customers.
"Fishing Hobbyist Application": An application can utilize this model to assist fish hobbyists in identifying and differentiating various types of fish feed (pakanikan), thus helping them provide the appropriate diet for their aquarium fish.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            pakanikan_dataset,
                            title = { pakanikan Dataset },
                            type = { Open Source Dataset },
                            author = { pakan },
                            howpublished = { \url{ https://universe.roboflow.com/pakan/pakanikan } },
                            url = { https://universe.roboflow.com/pakan/pakanikan },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { jun },
                            note = { visited on 2024-06-23 },
                            }