Redefining Disease Assessment in Raspberries: A Hybrid GAN-SVM Model for Detailed Intensity Measurement

This study presents a hybrid Generative Adversarial Network (GAN) and Support Vector Machine (SVM) model for accurately categorizing Raspberry Cane Disease (RCD) into four severity levels. Leveraging a dataset of 7,000 high-resolution images, the model achieves 98.8% accuracy. GANs generate synthetic images to address data scarcity, while SVMs ensure precise multi-class classification. The results demonstrate the model's effectiveness in disease severity assessment, highlighting its potential for broader agricultural applications.