Abstract
We suggest in this work that with the assistance of imaging processing, plant disease detection systems can automatically detect the symptoms that occur on the leaves and stem of a plant, which in turn assists in the cultivation of healthy plants on a farm. These systems monitor the plant, including its leaves and stem, and if there is any variation noticed from the plant's characteristic attributes, that variation will be automatically identified and the user will also be informed of it. An analysis and evaluation of the disease detection technologies currently used in plant species has been presented here. The most recent advancement in the field of deep learning, known as the convolutional neural network (CNN), has significantly improved the accuracy of picture classification. This thesis is based on the pre-trained deep learning-based method for identifying plant illnesses. It was motivated by CNN's success in the picture classification field. The contribution of this work can be b