Chilli Computer Vision Project
Updated a year ago
Metrics
Here are a few use cases for this project:
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Agricultural Management: The model can help in identifying chilli-weed classes in a field. By differentiating between crops and weeds, it can aid farmers in more effective and precision agriculture, reducing labor and time in weeding operations, and improving overall crop yield.
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Botanical Research: The "Chilli" model can be used in botanical studies to understand the invasion patterns of various types of weeds in chilli crops. It can help assess the impact of different weed species on crop growth.
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Herbicide Development: The model can assist in herbicide research and development. By identifying specific weed types that infest chilli crops, companies can work to design more targeted and effective herbicide solutions.
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Agricultural Education: The model could be used as teaching material in agriculture-based education. Students can utilize the technology to improve their understanding of weed identification and its impact on crop cultivation.
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Environmental Monitoring: By tracking weed spread, the "Chilli" model can be used in ecological investigations to monitor changes in local biodiversity, contributing to the surveillance and response systems for invasive weeds.
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Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
chilli-llhbh_dataset,
title = { Chilli Dataset },
type = { Open Source Dataset },
author = { project },
howpublished = { \url{ https://universe.roboflow.com/project-cuwpe/chilli-llhbh } },
url = { https://universe.roboflow.com/project-cuwpe/chilli-llhbh },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { aug },
note = { visited on 2024-11-21 },
}