Sesame Object Detection Dataset and Pre-Trained Model by new-workspace-mwunv

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Explore Dataset

Here are a few use cases for this project:

Agricultural Disease Management: Sesame can be used by farmers, agricultural scientists, and agronomists to detect and monitor the prevalence of bacterial leaf blight and powdery mildew in crops, enabling them to make timely interventions and reduce yield loss.
Smart Farming Systems Integration: Sesame can be integrated into smart farming systems, including drones, robotics or IoT devices, to automatically monitor crops' health, identify disease outbreaks early on, and automatically target the affected areas for treatment without human intervention.
Plant Disease Research: Researchers can use Sesame to study the transmission patterns and prevalence of bacterial leaf blight and powdery mildew, allowing them to better understand these diseases and develop more effective prevention and treatment strategies.
Educational Tool: Sesame can be used as an educational tool to train students, hobbyists, and other individuals interested in learning about plant diseases identification and management. Users can upload images of affected plants, and Sesame will provide instant feedback on the disease class, improving their knowledge and skills in the process.
Mobile Application for Farmers and Gardeners: A mobile application powered by Sesame could help farmers and gardeners to quickly identify bacterial leaf blight and powdery mildew in their fields or gardens. By simply taking a photo of a leaf with their smartphone, users would receive accurate diagnostic information for immediate action, ensuring healthier plants and better yields.

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{
                            sesame_dataset,
                            title = { Sesame Dataset },
                            type = { Open Source Dataset },
                            author = { new-workspace-mwunv },
                            howpublished = { \url{ https://universe.roboflow.com/new-workspace-mwunv/sesame } },
                            url = { https://universe.roboflow.com/new-workspace-mwunv/sesame },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { jul },
                            note = { visited on 2024-06-27 },
                            }