Weeds are one of the most harmful agricultural pests that have a significant impact on crops.
Weeds are responsible for higher production costs due to crop waste and have a significant …

Background and aim: Machine learning methods are examined by many researchers to
identify weeds in crop images captured by drones. However, metaheuristic optimization is …

Increased crop productivity is largely dependent on weed control, thus making weed
detection an important aspect of smart agriculture systems. To spray pesticides, it is …

Selective agrochemical spraying is a highly intricate task in precision agriculture. It requires
spraying equipment to distinguish between crop (plants) and weeds and perform spray …

There are several major threats to crop production. As herbicide use has become overly
reliant on weed control, herbicide-resistant weeds have evolved and pose an increasing …

A crop monitoring system was developed for the supervision of organic fertilization status on
tomato plants at early stages. An automatic and nondestructive approach was used to …

Crop and weeds identification is of important steps towards the development of efficient
automotive weed control systems. The higher the accuracy of plant detection and …

The creeping perennial weed species Cirsium arvense (L.) Scop. occurs in patches.
Expanding creeping roots allow these patches to increase their covered area. This …

Object recognition in containers is extremely difficult for robots. Dynamic audio signals are
more responsive to an object's internal property. Therefore, we adopt the dynamic contact …

Eight experiments were carried out in Denmark to determine the yield loss of spring barley
due to Cirsium arvense in farmers' fields and to suggest and evaluate a novel approach for …