hornetv2 Object Detection Dataset and Pre-Trained Model by PIR

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Explore Dataset

Here are a few use cases for this project:

Pest Control Applications: The "hornetv2" could be used by pest control services to quickly locate and identify hornet presence in a specific area. This would allow for more efficient pest management and improved safety measures.
Biodiversity Analysis: Ecologists or environmental scientists could leverage the model to monitor hornet populations in different environments. This could aid in studies about the effects of environmental factors on hornet populations or in identifying endangered species.
Public Safety and Awareness: Local municipal authorities or park departments could utilize the tool to identify areas of high hornet activity in public spaces such as parks or beaches. This information could be used to increase public awareness, promoting safety and avoiding potential harm to the public.
Agricultural Monitoring: Farmers or gardeners could use "hornetv2" to monitor hornet activity in their farms or gardens. This could aid effective pest control, preventing loss of crops or plant damage.
Beekeeping: Beekeepers may use this model to detect the presence of hornets in their bee colonies. With early detection and differentiation between bees and hornets, beekeepers can protect their hive from potential hornet invasions.

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{
                            hornetv2_dataset,
                            title = { hornetv2 Dataset },
                            type = { Open Source Dataset },
                            author = { PIR },
                            howpublished = { \url{ https://universe.roboflow.com/pir/hornetv2 } },
                            url = { https://universe.roboflow.com/pir/hornetv2 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { mar },
                            note = { visited on 2024-04-28 },
                            }