Plant Leaf Disease Classification Using GAN

Plant diseases can be precisely detected using field leaves. However, collecting a sufficient number of unhealthy leaf images from various plants can be challenging, resulting in an unbalanced dataset. To address this issue, Generative Adversarial Networks (GANs) are employed. GANs consist of a generator and discriminator neural network. The generator creates synthetic data, while the discriminator distinguishes between real and generated samples. By adding GAN-generated images to an unbalanced dataset, the model’s performance improves, resulting in a more balanced dataset. This approach aids in accurate plant disease detection and benefits agriculture.