livestalk Object Detection Dataset and Pre-Trained Model by omarkapur@berkeley.edu

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Explore Dataset

Here are a few use cases for this project:

Livestock Management: Livestalk can be used by farmers and livestock owners to monitor and identify different cow classes, ensuring proper tracking and care for each animal. This can help in preventing misidentification, loss, theft, and improving overall herd health.
Animal Conservation & Research: Researchers and wildlife conservationists can use the Livestalk model to study and monitor cow populations in various ecosystems, assisting in efforts to preserve and protect native species and their habitats.
Smart Farming Technology: The Livestalk model can be integrated into smart farming systems, enabling automatic identification and sorting of different cow classes, enhancing efficiency, and reducing labor requirements in modern agriculture practices.
Veterinary Medicine & Diagnostics: Veterinarians can use the Livestalk model to assist in identifying specific cow classes, aiding in the diagnosis and treatment of illnesses related to certain species or breeds, improving overall animal health and well-being.
Educational & Public Awareness: The Livestalk computer vision model can be used in educational settings as a learning tool for students and the general public interested in understanding and identifying different cow classes, promoting public awareness about biodiversity, and encouraging the appreciation of the natural world.

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{
                            livestalk_dataset,
                            title = { livestalk Dataset },
                            type = { Open Source Dataset },
                            author = { omarkapur@berkeley.edu },
                            howpublished = { \url{ https://universe.roboflow.com/omarkapur-berkeley-edu/livestalk } },
                            url = { https://universe.roboflow.com/omarkapur-berkeley-edu/livestalk },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-04-27 },
                            }