The efficient identification of rice pests and diseases is crucial for preventing crop damage.
To address the limitations of traditional manual detection methods and machine learning …

In order to achieve accurate, fast, and robust recognition of blueberry fruit maturity stages for
edge devices such as orchard inspection robots, this research proposes a lightweight …

Because the growth of mangoes is often affected by pests and diseases, the application of
object detection technology can effectively solve this problem. However, deploying object …

The quality of cotton seed is of great significance to the production of cotton in the cotton
industry. In order to reduce the workload of the manual sorting of cotton seeds and improve …

Wheat spike detection is of great research importance for wheat yield estimation as well as
wheat quality management. For the detection of wheat spikes, object detection methods …

Nowadays, the expansion of people into intact primary areas has been observed alongside
an increase in the area of land devoted to crops, pastures, etc., which has led to the …

Accurate detection and localization of fruits within the canopy are crucial for various tasks,
such as perception for robotic harvesters, vision-based yield estimation, and early disease …

In recent years, advancements in computer vision (CV) and machine learning (ML) have
facilitated significant progress in the field of plant disease prediction and detection. The …

There is an increasing demand for efficient and precise plant disease detection methods that
can quickly identify disease outbreaks. For this, researchers have developed various …

The location and number of individual fruit trees (IFTs) are critical for investigations on
planting areas, fruit yield predictions, and smart orchard planning and management. These …