Fruit detection and localization are essential for future agronomic management of fruit crops
such as yield prediction, yield mapping and automated harvesting. However, to perform …

Orchard pre-harvest yield data is important for fruit growers, which can be used for economic
benefit evaluation, management mode adjustment and so on. However, traditional manual …

In the complex environment of an orchard, changes in illumination, leaf occlusion, and fruit
overlap make it challenging for mobile picking robots to detect and locate oil-seed camellia …

The apple target recognition algorithm is one of the core technologies of the apple picking
robot. However, most of the existing apple detection algorithms cannot distinguish between …

Accurate count of fruits is important for producers to make adequate decisions in production
management. Although some algorithms based on machine vision have been developed to …

High-throughput phenotyping has been widely studied in plant science to monitor plant
growth and analyze the influence of genotypes and environment on plant growth. To meet …

Automatic detection of kiwifruit in the orchard is challenging because illumination varies
through the day and night and because of color similarity between kiwifruit and the complex …

Field robotic harvesting is a promising technique in recent development of agricultural
industry. It is vital for robots to recognise and localise fruits before the harvesting in natural …

Pallet racking is an essential element within warehouses, distribution centers, and
manufacturing facilities. To guarantee its safe operation as well as stock protection and …

Accurate identification of table grapes is crucial to the harvesting process of the grape
picking robot. This paper proposes an efficient grape detection model, YOLO-Grape, to solve …