Leaf Detection Computer Vision Project

FTBG GBE Technology Team

Updated 2 years ago

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Description

Here are a few use cases for this project:

  1. Plant Classification App: An application that allows botanists, horticulturists, or plant enthusiasts to classify various plants by using this model to identify their leaf types.

  2. Agricultural Automation Systems: This model could be integrated into agricultural bots to identify specific leaf types for targeted treatment, like pesticide application, in precision farming.

  3. Environmental Research: Researchers studying biodiversity or environmental change could use this model to automatically identify and record leaf types in large sets of data, accelerating their work.

  4. Landscape Architectural Design: Landscape architects might use this tool to help identify plants by leaves in their design areas for better planning and designing.

  5. Identification of Invasive Species: Conservationists and environmentalists can use this model to detect the presence of invasive plant species in an areaquickly by their leaf type.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            leaf-detection-vaggn_dataset,
                            title = { Leaf Detection Dataset },
                            type = { Open Source Dataset },
                            author = { FTBG GBE Technology Team },
                            howpublished = { \url{ https://universe.roboflow.com/ftbg-gbe-technology-team-jllp2/leaf-detection-vaggn } },
                            url = { https://universe.roboflow.com/ftbg-gbe-technology-team-jllp2/leaf-detection-vaggn },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-11-08 },
                            }
                        
                    

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