weeddetectorr Computer Vision Project
Here are a few use cases for this project:
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Agricultural Automation: Use the weed detector model to identify and classify types of weeds in crop fields, and accordingly apply the correct treatment or dispatch automated weed-removal machines. This use case can help increase crop yield and save resources in the farming industry.
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Botany Research: Use the model in scientific studies focusing on weed behavior, how they interact with certain environments, which are more prone to invade specific areas, etc. Helps in data collection and analysis for such studies.
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Environmental Management: Apply the weed detector model in parks, forests, or other green areas to monitor the invasion of harmful weed species and take necessary preventative actions.
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Gardening Assistance App: Integrate the model into a mobile app that can advise home gardeners or professional landscapers on the type of weed they're dealing with and offer advice on how to remove it or manage it.
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Biosecurity at Ports: Use the model to screen soil or plant samples at ports of entry to prevent the introduction of invasive weed species into new environments, assisting in the preservation of local biodiversity.
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{
weeddetectorr_dataset,
title = { weeddetectorr Dataset },
type = { Open Source Dataset },
author = { elf },
howpublished = { \url{ https://universe.roboflow.com/elf-wbesr/weeddetectorr } },
url = { https://universe.roboflow.com/elf-wbesr/weeddetectorr },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { feb },
note = { visited on 2024-05-15 },
}
Connect Your Model With Program Logic
Find utilities and guides to help you start using the weeddetectorr project in your project.
