Roboflow Universe Erin Tomassoni Workspace Bee Health Data

Bee Health Data Computer Vision Project

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This model assesses honeybee health indicators. Using 3 classes (Healthy, pollen carrier, and infested) it can determine the overall health variables of a hive. The data used includes examples of European (Apis mellifera) and Italian (Apis mellifera ligustica) honey bees. These two species are common in the United States, although it is important to note small variation in species physiological features could make the model less accurate. It is recommended to use isolated, close up images of bees for best accuracy. This model was created for a class assignment in AI and Natural History at St. Mary’s College of Maryland.

Datasets Used: https://www.kaggle.com/code/gcdatkin/pollen-detection-in-honeybee-images/input https://zenodo.org/records/4085044 https://www.tensorflow.org/datasets/catalog/bee_dataset https://www.kaggle.com/datasets/jenny18/honey-bee-annotated-images

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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{
                            bee-health-data_dataset,
                            title = { Bee Health Data Dataset },
                            type = { Open Source Dataset },
                            author = { Erin Tomassoni Workspace },
                            howpublished = { \url{ https://universe.roboflow.com/erin-tomassoni-workspace/bee-health-data } },
                            url = { https://universe.roboflow.com/erin-tomassoni-workspace/bee-health-data },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { apr },
                            note = { visited on 2024-05-01 },
                            }