With increasing population, the demand for agricultural productivity is rising to meet the goal
of “Zero Hunger”. Consequently, farmers have optimized the agricultural activities in a …

With the rise of new technologies, such as the Internet of Things, raising the productivity of
agricultural and farming activities is critical to improving yields and cost-effectiveness. IoT, in …

Plant diseases are considered one of the main factors influencing food production and
minimize losses in production, and it is essential that crop diseases have fast detection and …

Improvement of deep learning algorithms in smart agriculture is important to support the
early detection of plant diseases, thereby improving crop yields. Data acquisition for …

It has been noted that disease detection approaches based on deep learning are becoming
increasingly important in artificial intelligence‐based research in the field of agriculture …

Deep learning is known as a promising multifunctional tool for processing images and other
big data. By assimilating large amounts of heterogeneous data, deep-learning technology …

In recent years, there have been significant achievements in object classification with
various techniques using several deep learning architectures. These architectures are now …

The Kingdom of Saudi Arabia is considered to be one of the world leaders in olive
production accounting for about 6% of the global olive production. Given the fact that 94% of …

This study's foremost objectives were to scrutinize how unexpected weather affects
agricultural output and to assess how well AI-based machine learning and deep leaning …

The olive tree is affected by a variety of diseases. To identify these diseases, many farmers
typically use traditional methods that require a lot of effort and specialization. These methods …