segmentation diseases

Monitoring crops

Instance Segmentation

1

Monitoring crops Computer Vision Project

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Here are a few use cases for this project:

  1. Predictive Agriculture: Use the "Monitoring crops" model for early detection of diseases and pests in agricultural fields, allowing farmers to take preventative measures to minimize crop loss and increase crop yield.

  2. Smart Greenhouses: Implement the model in various indoor growing environments, such as greenhouses or vertical farms, to monitor plant health and detect common diseases or infestations, enabling more efficient crop production and better control of growth conditions.

  3. Automated Drones: Equip drones with the "Monitoring crops" model for large-scale and accurate monitoring of agricultural land. Drones can regularly survey the fields, identifying the presence of specific diseases, and guiding targeted treatment to high-risk areas.

  4. Remote Consultation for Farmers: Integrate the "Monitoring crops" model with mobile applications or web platforms, where farmers can upload images of their crops to get instant feedback on plant health and receive recommendations for appropriate treatment methods.

  5. Agricultural Research: Utilize the model for collecting and analyzing data on the prevalence of plant diseases and pests in various geographical locations and under different climate conditions, further informing agricultural research and creating knowledge on disease patterns and effective interventions.

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{
                            monitoring-crops_dataset,
                            title = { Monitoring crops Dataset },
                            type = { Open Source Dataset },
                            author = { segmentation diseases },
                            howpublished = { \url{ https://universe.roboflow.com/segmentation-diseases/monitoring-crops } },
                            url = { https://universe.roboflow.com/segmentation-diseases/monitoring-crops },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { nov },
                            note = { visited on 2024-02-26 },
                            }
                        

Connect Your Model With Program Logic

Find utilities and guides to help you start using the Monitoring crops project in your project.

Last Updated

a year ago

Project Type

Instance Segmentation

Subject

yolov7

Classes

Angular leaf spot Anthracnose fruit rot Bean rust Blossom blight Gray mold Healthy Leaf mold Powdery Mildew Fruit Powdery Mildew Leaf Rust early Spider mites Strawberry leafspot Strawberry angular leafspot Strawberry leafspot

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License

CC BY 4.0