Working of the Model

Our system accepts plant leaf images as input and produces a classification output corresponding to one of the 22 designated classes. In recent years, deep neural networks have demonstrated remarkable success in various domains as powerful tools for end-to-end learning. These networks learn to establish a mapping between an input (e.g., an image of a diseased plant) and a corresponding output (e.g., a specific crop-disease diagnosis). The interconnected mathematical nodes within a neural network process numerical inputs from incoming connections, generating numerical outputs via outgoing connections.