transfer learning

In agriculture, early detection of crop diseases is imperative for sustainability and maximizing yields.  Rooted in Agriculture 4.0, our innovative approach  combines pre-trained Convolutional Neural Networks (CNNs) models with data-driven solutions to address global challenges related to water scarcity.  By integrating the combined $L_{1}/L_{2}$ regularization technique to our model layers, we enhance their flexibility, reducing the risk of the overfitting effect of the model.  In the orange dataset used in our experiments, we have 1790 orange images, including a class

A Question Generation System (QGS) is a sophisticated piece of AI technology designed to automatically generate questions from a given text, document, or context.  Recently, this technology has gained significant attention in various fields, including education, and content creation.  As AI continues to evolve, these systems are likely to become even more advanced and viewed as an inherent part of any modern e-learning or knowledge assessment system.  In this research paper, we showcase the effectiveness of leveraging pre-trained checkpoints for Arabic questions generat