Loss function computation using machine learning algorithms based on the effects of natural disasters and plant diseases on plant growth

Abstract

Many Machine Learning(ML) architectures have been in use for detecting soil structure, plant diseases and other plant related tasks for many years. So here using Machine Learning we are trying to compute a 'Loss Function' which will provide a Loss factor value between (0-1) for determining how different Natural Disasters(particular weather factors) and Plant Diseases affect plant structure (growth) and get an output of how much of the crop is affected. Moreover, the Loss function mainly will help us get a value which will quickly determine plant growth in a particular condition. In addition, for the Disease detection we are going to use images with real life backgrounds which will ensure that there are plants in a particular background and we can still detect the disease. Therefore, our main target will be making the 'Loss Function' depending on two factors namely Natural Disasters (particular weather factors) and Plant Diseases. By using our 'Loss Function' a Loss factor value will be given as output which considers effects of these two parameters on plant growth.