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

A tomato automatic detection method based on an improved YOLOv8s model is proposed to
address the low automation level in tomato harvesting in agriculture. The proposed method …

Plant phenotyping is the study of complex plant traits to evaluate its status depending on the
life-cycle conditions. Often, these evaluations are carried out by human operators, and the …

The generation of food production that meets the rising demand for food and ecosystem
security is a big challenge. With the development of Artificial Intelligence (AI) models, there …

The harvesting operation is a recurring task in the production of any crop, thus making it an
excellent candidate for automation. In protected horticulture, one of the crops with high …

Effective identification of tomato plant traits is crucial for timely monitoring and evaluating
their growth and harvest. However, conducting stress experiments on multiple tomato …

The foundation of effectively predicting plant disease in the early stage using deep learning
algorithms is ideal for addressing food insecurity, inevitably drawing researchers and …

Agricultural robots are one of the important means to promote agricultural modernization
and improve agricultural efficiency. With the development of artificial intelligence technology …

To realize tomato growth period monitoring and yield prediction of tomato cultivation, our
study proposes a visual object tracking network called YOLO-deepsort to identify and count …

This paper presents the development of an autonomous harvesting robot system for tomato,
a representative crop cultivated in the facility horticulture smart farm. The automated …