YOLO for Detecting Crop Diseases
Idea Description
YOLO (You Only Look Once) is an algorithm that uses Neural Networks to provide real-time object detection in images or video frames. This algorithm is popular because of its speed and accuracy.
This idea is going to use YOLOv8 which is the latest model of YOLO for detecting crop diseases in Oman. YOLO can provide farmers in Oman with a powerful tool to monitor and manage their crops, helping to increase efficiency, reduce waste, and improve the overall yield and quality of their products. Also, it can monitor crops and detect changes in plant growth, health, and quality. For example, YOLO can detect the presence of weeds or disease in crops, allowing farmers to take action before the problem spreads.
In Oman, crops such as dates, citrus fruits, and vegetables are grown. Common plant diseases in Oman include powdery mildew, downy mildew, black rot, and citrus canker. These diseases can cause significant damage to crops and reduce yields. By using Computer Vision Algorithms like YOLO, farmers and researchers can detect these diseases early on and take appropriate measures to control or treat them. This can help prevent the spread of the disease and minimize crop losses. Moreover, they can reduce the use of pesticides and other harmful chemicals.
Challenges The Idea is Addressing
1- Wastes of diseased crops and plants. 2- Crops Infections. 3- Dependence on pesticides and other harmful chemicals. 4- Difficulties of identifying local crop diseases.
Benefits of Idea Implementation
1- Fast and Early Detection. 2- High Accuracy Rate. 3- Reducing Dependence on pesticides. 4- Improved Crop Quality. 5- Improved Food Security. 6- Monitoring Diseases Outbreaks.
Proposed Number of Team Members
5
Team Members
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167869223223Manuscript.pdf
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Last Update:- 13 March 2023
