Multi Label Classification of Weed Species Classification Dataset and Pre-Trained Model by KBS

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Explore Dataset

Here are a few use cases for this project:

Agriculture and Farming: The model could be used by agronomists and farmers to identify different kinds of weeds in their fields to implement appropriate weed treatment strategies. This would be particularly helpful in large-scale farms to conduct timely and efficient weed identification and treatment.
Garden Management: Gardeners and homeowners could use the model to identify weed species in their gardens or yards to maintain healthy plants and grass by eliminating invasive weed species.
Land Survey and Biodiversity Studies: Ecologists and land surveyors could use the model in field surveys to catalog weed species diversity in a particular area, thereby aiding in environmental research and conservation efforts.
Herbicide Development: Researchers and scientists involved in developing herbicides can utilize this model to test their products' effectiveness against specific weed species identified by the model.
Greenhouse Management: The model can be implemented in greenhouses or indoor plantations to monitor and control the growth of unwanted weed species, helping maintain the optimal development of cultivated plants.

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{ multi-label-classification-of-weed-species_dataset,
    title = { Multi Label Classification of Weed Species Dataset },
    type = { Open Source Dataset },
    author = { KBS },
    howpublished = { \url{ https://universe.roboflow.com/kbs-sillb/multi-label-classification-of-weed-species } },
    url = { https://universe.roboflow.com/kbs-sillb/multi-label-classification-of-weed-species },
    journal = { Roboflow Universe },
    publisher = { Roboflow },
    year = { 2023 },
    month = { may },
    note = { visited on 2023-12-09 },
}