Computer vision (CV) combined with a deep convolutional neural network (CNN) has
emerged as a reliable analytical method to effectively characterize and quantify high …

Researchers have recently focused their attention on vision-based hand gesture
recognition. However, due to several constraints, achieving an effective vision-driven hand …

Although convolutional neural network (CNN) paradigms have expanded to transfer
learning and ensemble models from original individual CNN architectures, few studies have …

Rice is considered one the most important plants globally because it is a source of food for
over half the world's population. Like other plants, rice is susceptible to diseases that may …

Plant diseases and insect pests cause a significant threat to agricultural production. Early
detection and diagnosis of these diseases are critical and can reduce economic losses. The …

Rice is a staple food for roughly half of the world's population. Some farmers prefer rice
cultivation to other crops because rice can thrive in a wide range of environments. Several …

Tomato leaf infections are a common threat to long-term tomato production that affects many
farmers worldwide. Early detection, treatment, and solution of tomato leaf specificity are …

There is an incredible progress in machine learning applications in the field of agricultural
research. Detection of various diseases, deficiencies, and factors impacting crops' …

Computer vision-based automation has become popular in detecting and monitoring plants'
nutrient deficiencies in recent times. The predictive model developed by various researchers …

Rice is the most important cereal food crop in the world, and half of the world's population
uses rice as a staple food for its energy source. The yield production qualities and quantities …