Weeds have a significant impact on sesame throughout its early stages of development, thus
they must be rigorously controlled. However, the shape of sesame seedlings and weeds are …

The advancement of computer vision technology has allowed for the easy detection of
weeds and other stressors in turfgrasses and agriculture. This study aimed to evaluate the …

Pine wilt nematode disease is a devastating forest disease that spreads rapidly. Using drone
remote sensing to monitor pine wilt nematode trees promptly is an effective way to control …

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 …

The accurate identification of weeds in peanut fields can significantly reduce the use of
herbicides in the weed control process. To address the identification difficulties caused by …

In recent years, automatic weed control has emerged as a promising alternative for reducing
the amount of herbicide applied to the field, instead of conventional spraying. This method is …

Accurate identification of crop diseases can effectively improve crop yield. Most current crop
diseases present small targets, dense numbers, occlusions and similar appearance of …

Poppy (also common poppy or corn poppy; Papaver rhoeas L., PAPRH) is one of the most
harmful weeds in winter cereals. Knowing the precise and accurate location of weeds is …

A YOLOX convolutional neural network-based weeding robot was designed for weed
removal in corn seedling fields, while verifying the feasibility of a blue light laser as a non …

Soybean in the field has a wide range of intermixed weed species and a complex
distribution status, and the weed identification rate of traditional methods is low. Therefore, a …