<![CDATA[Agriculture is the most important sector in developing countries, so the main source of concern for farmers is plant diseases that lead to a lack of production and a waste of money and crops. In this paper, a system using computer-assisted convolutional neural networks (CNN) with camera is developed to characterize diseases of citrus trees. This proposed system can help farmers to increase and improve the quality of their agricultural productivity. In addition to reducing the spread of the disease through early detection. Citrus leaf dataset was created to train and test the model because citrus is one of the main crops in Iraq. The results of the experiment shown that the implemented CNN achieved high classification accuracy of (92%) with fewer parameters, making it flawless and promising outcomes.]]>
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