This review paper addresses the critical need for advanced rice disease detection methods
by integrating artificial intelligence, specifically convolutional neural networks (CNNs). Rice …

The proliferation of IoT devices requires innovative approaches to gaining insights while
preserving privacy and resources amid unprecedented data generation. However, FL …

Rice is an important staple food in Asia. It is produced and consumed in large quantities. It
contributes to 15% of protein intake and 21% of total per capita energy intake in the region …

This research aims to evaluate and compare the performance of several deep learning
architectures, especially InceptionV3 and InceptionResNetV2, with other models, such as …

When agricultural experts explore the use of artificial intelligence technology to identify and
detect crop diseases, they mainly focus on the research of a stable environment, but ignore …

Rice (Oryza sativa L.) is one type of cultivated plant that has the ability to adapt to various
conditions and is a main ingredient of food in many countries, especially in Asia, including …

In response to the increasing global demand for food, feed, fiber, and fuel, digital agriculture
is rapidly evolving to meet these demands while reducing environmental impact. This …

Science regarding plants has experienced significant progress, especially in the study of
medicinal plants. Medicinal plants have been used in medicine and are still an important …

This paper presents an innovative approach to the automatic detection of rice leaf diseases
using advanced deep learning techniques, specifically focusing on the use of convolutional …

Apple orchards are of significant importance in the global agricultural sector, but they are
vulnerable to a range of diseases that have the potential to cause diminished crop …