FARMieNG Object Detection Dataset and Pre-Trained Model by Alienor Duron

Images

135 images

Explore Dataset

Here are a few use cases for this project:

Precision Agriculture: FARMieNG can be used by farmers or agronomists to monitor crop health in real-time, enabling better decision-making in the fields. Early detection of diseases or unhealthy plants can prevent further spread and help farmers take appropriate action to maintain yield and reduce losses.
Greenhouse Management: This computer vision model can be applied in greenhouses or indoor farming systems to keep a close eye on plant health. By detecting potential issues early on, greenhouse operators can take corrective measures to ensure optimal plant growth and productivity.
Plant Disease Database: FARMieNG could be utilized to build a comprehensive plant disease and pest database, aiding researchers, and agriculture professionals in studying and developing more effective control methods for various plant diseases and pests.
Remote Sensing for Agriculture: Coupling FARMieNG with satellite or drone imagery, governments, and organizations can assess the overall health of crops in agricultural areas. This information can be used for crop yield prediction, disaster management, and to develop strategies to tackle food security issues.
Educational Tool: FARMieNG could serve as an educational resource for students, researchers, or hobbyist gardeners to learn more about plant diseases and overall plant health. By gaining better understating of these conditions, users may develop effective preventive measures and improve their plant care practices.

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{
                            farmieng_dataset,
                            title = { FARMieNG Dataset },
                            type = { Open Source Dataset },
                            author = { Alienor Duron },
                            howpublished = { \url{ https://universe.roboflow.com/alienor-duron/farmieng } },
                            url = { https://universe.roboflow.com/alienor-duron/farmieng },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2021 },
                            month = { oct },
                            note = { visited on 2024-04-27 },
                            }