COCOA DISEASE DETECTION Computer Vision Project

Pcshnst

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Classes (5)
BLACKPOD
FROSTYPOD
HEALTHY
MIRID
busukbuah-monilia
Description

Here are a few use cases for this project:

  1. Agricultural Consultancy: The "COCOA DISEASE DETECTION" model can be used by agricultural consultancies to remotely monitor cocoa plantations, helping them to provide sound advice to farmers about disease prevention, early detection and appropriate treatment.

  2. Pesticide Companies: This model can serve as a diagnostic tool for companies developing pesticides for specific cocoa diseases. By pinpointing the type of disease afflicting the plant, they can tailor their products more efficiently and effectively.

  3. Greenhouse Farming: In a controlled agricultural environment, such as a greenhouse, the model could be used for real-time monitoring of cocoa plants. This would help in early detection of diseases and swift mitigation.

  4. Agricultural Research Institutions: These organisms could use this model for studies on disease progression and the effectiveness of different treatments or resistant crop varieties.

  5. Mobile App for Cocoa Farmers: The "COCOA DISEASE DETECTION" model could be deployed in a mobile app that would permit farmers to identify diseases simply by taking a picture of their cocoa plants. This would help farmers detect and treat diseases early, increasing their overall productivity.

Supervision

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Cite This Project

LICENSE
MIT

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

                        @misc{
                            cocoa-disease-detection-ysgtm_dataset,
                            title = { COCOA DISEASE DETECTION Dataset },
                            type = { Open Source Dataset },
                            author = { Pcshnst },
                            howpublished = { \url{ https://universe.roboflow.com/pcshnst/cocoa-disease-detection-ysgtm } },
                            url = { https://universe.roboflow.com/pcshnst/cocoa-disease-detection-ysgtm },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { aug },
                            note = { visited on 2024-09-22 },
                            }