Nest Finder Computer Vision Project
Here are a few use cases for this project:
-
Bird Conservation Projects: Conservationists could use the Nest Finder model to monitor and track specific bird species in different geographical locations. It could help them understand nesting patterns and contribute to conservation efforts.
-
Climate and Habitat Studies: Ecologists can utilize the model to study the impacts of climate change and habitat destruction on birdlife by observing changes in nest placement and frequency.
-
Birdwatching Apps: An interactive birdwatching app could use this model to help users identify specific bird nests and learn more about bird species they're observing.
-
Wildlife Documentaries and Research: Filmmakers or researchers studying avian wildlife can use the model to identify bird nest types, aiding in accurate information dissemination and contributing to qualitative research.
-
Pest and Invasive Species Management: The model could be used to identify the nests of invasive bird species, allowing for more efficient management and control of such species.
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{
nest-finder_dataset,
title = { Nest Finder Dataset },
type = { Open Source Dataset },
author = { CMEE },
howpublished = { \url{ https://universe.roboflow.com/cmee/nest-finder } },
url = { https://universe.roboflow.com/cmee/nest-finder },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jul },
note = { visited on 2024-06-23 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the Nest Finder project in your project.