Weed Detection v1 Computer Vision Project
Updated a year ago
Metrics
Here are a few use cases for this project:
-
Precision Agriculture: The model could be used to identify weeds in farmers' fields to automatically monitor crop health and target weed control measures, increasing crop productivity and reducing the use of herbicides.
-
Robotic Weeding: The model can be integrated into an agricultural robot to perform selective weeding, distinguishing between crop plants (such as soybeans) and different types of weeds.
-
Environmental Research: Researchers could use this model to track the spread of invasive weed species over time and monitor the effectiveness of control measures.
-
Botanical Education: The model could be incorporated into educational tools or apps to help students and hobbyists learn to identify different types of plants and understand the impact of weeds on plant ecosystems.
-
Gardening Assistance: Gardeners can use an app powered by this model to identify weeds in their gardens, assisting in maintenance and plant health.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
weed-detection-v1-vzg5e_dataset,
title = { Weed Detection v1 Dataset },
type = { Open Source Dataset },
author = { Dr Zhang Research team },
howpublished = { \url{ https://universe.roboflow.com/dr-zhang-research-team/weed-detection-v1-vzg5e } },
url = { https://universe.roboflow.com/dr-zhang-research-team/weed-detection-v1-vzg5e },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { jun },
note = { visited on 2024-11-21 },
}