Advanced Detection

Abstract

In the present scenario, due to climate change, farmers crops get fungi due to bacteria since soil temperatures change very rapidly according to sudden climate changes for which the crop is getting spoiled. At this advanced era, disease can be detected early so that crops are safe. Different types of fungi-bacterial disease will be detected and prevented by machine learning-based predicted deterministic probabilistic and artificial technology-based CNN for colour changes in plants. This chapter described machine learning techniques and proposed modified algorithms to identify and classify plant diseases. Deep neural network (DNN) models and algorithms are used to improve object accuracy and entropy to reduce the complexity of computational processes and improve the features during deep learning processes (e.g., modified deep neural network [MDNN]). Additionally, they support dynamic feature extraction DSURF and classifier combinations for creating image clusters with the help of clustering and deterministic probability.