Plant diseases present a substantial threat to global food security, as they have the potential
to significantly reduce crop yields. Detecting these plant diseases early and managing them …

Plant disease identification is critical for lowering output losses and guaranteeing food
security. This study looks at the use of four common transfer learning models for early plant …

Plant leaf diseases pose significant threats to crop yield and agricultural sustainability,
making early and accurate detection crucial for effective disease management. In recent …

The early diagnosis of leaf diseases is essential for maintaining the health and yield of
crops. With advancements in deep learning and computer vision, transfer learning has …

The early diagnosis of leaf diseases is essential for maintaining the health and yield of
crops. With advancements in deep learning and computer vision, transfer learning has …

Plant diseases have a disastrous impact on the safety of food production, and they can
cause a significant reduction in both the quality and quantity of agricultural products. In …

Plant diseases are a significant hazard to feeding a growing population, but timely detection
is challenging due to a lack of infrastructure in many world regions. Finding and detecting …

Plant diseases pose a significant danger to global food security by reducing farmer output
and causing an economic crisis. Timely and precise illness identification is critical for …

Plant diseases are a principal threat to the safety of food. In agriculture sectors, it is the
greatest challenge to identify plant diseases. The state-of-the-art Convolutional Neural …

This paper investigates the use of Convolutional Neural Networks (CNNs) for plant disease
diagnosis, utilizing the notion of transfer learning to develop a deep CNN network at a low …