Detection of Malus Plant Infection Using Fifteen Layer Deep Convolutional Neural Network Model

Apple (scientifically malus domestica) is the fruit which is having high quality of nutrients. For a human being, Fruit consumption is the necessity for getting the nutrients. If it is found out that fruit is affected by some infectious agents, it can harm the health as well as wealth of the human. In terms of apple, farmers whose earnings are dependent on the production, will get economical loss, further financially state and country loss. Here, the proposed model is used to detect the symptoms of disease present in apple orchard with the help of apple leaves using fifteen layer deep convolutional neural network model. In a form of data set that is used here are of four categories such as apple scab, apple powdery mildew, apple rust, and apple healthy. The outcome of the model is giving accuracy and validation accuracy 97.91 and 97.8% respectively.