An Improved Pear Disease Classification Approach Using Cycle Generative Adversarial Network

This article discusses the use of machine learning and deep learning approaches in plant disease detection and classification. It specifically focuses on the use of a Cycle Generative Adversarial Network (CycleGAN) to overcome limitations in available data and improve classification accuracy. The results showed a 7% increase in accuracy compared to traditional CNN models.