beekeeping_step1 Object Detection Dataset and Pre-Trained Model by AI Clinic Beekeeping

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Explore Dataset

Here are a few use cases for this project:

Bee Conservation Research: Conservationists can use the "beekeeping_step1" model to identify specific bee species and monitor their activities. This can be used to understand the behavior, population dynamics, and potential threats to these species.
Beehive Management: Beekeepers can apply the model to quickly identify bee classes, helping them to understand the health and composition of their hives. For example, detecting an unusual number of drone bees could indicate a problem in the hive.
Agriculture and Pollination Studies: In agricultural settings, the model could be employed to monitor and study bee populations and their behaviors. This data could provide insights into the effectiveness of their pollination, and guide strategies to enhance crop yields.
Bee Behavior Research: The model can be used to track the activities of different types of bees, giving entomologists and researchers valuable data about their daily routines, interactions, and behaviors.
Educational Tools: The model could be utilized to create interactive educational materials or applications. Users could learn about different bee classes, their roles in the ecosystem, and the basics of beekeeping.

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.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            beekeeping_step1-5n131_dataset,
                            title = { beekeeping_step1 Dataset },
                            type = { Open Source Dataset },
                            author = { AI Clinic  Beekeeping },
                            howpublished = { \url{ https://universe.roboflow.com/ai-clinic-beekeeping/beekeeping_step1-5n131 } },
                            url = { https://universe.roboflow.com/ai-clinic-beekeeping/beekeeping_step1-5n131 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { nov },
                            note = { visited on 2024-04-25 },
                            }