Population growth, climate change, and the worldwide COVID-19 pandemic are imposing
increasing pressure on global agricultural production. The challenge of increasing crop yield …

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 …

Recent advances in communication technologies with the emergence of connected objects
have changed the agricultural area. In this new digital age, the development of artificial …

Deep learning (DL) represents the golden era in the machine learning (ML) domain, and it
has gradually become the leading approach in many fields. It is currently playing a vital role …

Precision farming aims to optimizing the crop production process and managing sustainable
supply chain practices as more efficient and reasonable as possible. Recently, various …

Accurate, rapid, and smart pest recognition and detection are important for crop protection
and management. Existing deep learning-based pest detection algorithms often require high …

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

Strawberry powdery mildew (PM) is the main disease affecting the yield and quality of
strawberries in recent years, which always appears on the back side of leaves in the early …

Traditional pest detection methods are challenging to use in complex forestry environments
due to their low accuracy and speed. To address this issue, this paper proposes the …

The accurate and robust crop pest detection system is an important step to enable the
reliable forecasting of agricultural pest in the community of precision agriculture, attracting …