The growing population and effect of climate change have put a huge responsibility on the
agriculture sector to increase food-grain production and productivity. In most of the countries …

Insect pest is one of the main causes affecting agricultural crop yield and quality all over the
world. Rapid and reliable insect pest monitoring plays a crucial role in population prediction …

Controlled environment agriculture (CEA) is an unconventional production system that is
resource efficient, uses less space, and produces higher yields. Deep learning (DL) has …

Globally, insect pests are the primary reason for reduced crop yield and quality. Although
pesticides are commonly used to control and eliminate these pests, they can have adverse …

This paper explores the utilization of innovative technologies such as RGB cameras, drones,
and computer vision algorithms, for monitoring pests in orchards, with a specific focus on …

Deep learning algorithms, such as convolutional neural networks (CNNs), have been widely
studied and applied in various fields including agriculture. Agriculture is the most important …

Crop pests are to blame for significant economic, social, and environmental losses
worldwide. Various pests have different control strategies, and precisely identifying pests …

Frequent outbreaks of agricultural pests can reduce crop production severely and restrict
agricultural production. Therefore, automatic monitoring and precise recognition of crop …

Insect pest management is one of the main ways to improve the crop yield and quality in
agriculture and it can accurately and timely detect insect pests, which is of great significance …

With the escalating global challenges of food security and resource sustainability, innovative
solutions like deep learning and computer vision are transforming agricultural practices by …