With rich annotation information, object detection-based automated plant disease diagnosis
systems (eg, YOLO-based systems) often provide advantages over classification-based …

Automation of agriculture with the use of cutting-edge technology is a growing research
area. It addresses the issue of better yields and tries to mitigate the negative impact due to …

The development of practical and robust automated diagnostic systems for identifying plant
pests is crucial for efficient agricultural production. In this paper, we first investigate three key …

Recently, object detection methods (OD; eg, YOLO-based models) have been widely utilized
in plant disease diagnosis. These methods demonstrate robustness to distance variations …

Although many image-based plant disease diagnosis systems have reported high
diagnostic performance recently, most of them do not seem to have a proper separation …

Recent studies on plant disease diagnosis using machine learning (ML) have highlighted
concerns about the overestimated diagnostic performance due to inappropriate data …

Automatic diagnosis of plant diseases using images is a fine-grained task, and disease
symptoms are often ambiguous and highly variable. Pre-extraction of the region of interest …

Plants must be checked at an early stage of their life cycle in order to avoid illnesses. Visual
observation, which takes longer, and costly expertise are the conventional approach utilised …

抄録 In recent years, data “generation” techniques using generative adversarial networks
(GANs), in which multiple neural networks learn in an adversarial manner, have achieved …