Weed control is among the most challenging issues for crop cultivation and turf grass
management. In addition to hosting various insects and plant pathogens, weeds compete …

Deep learning methods such as convolutional neural networks (CNN) have become popular
for addressing crops and weeds classification problems in agricultural robotics. However, to …

Plants and trees are essential for the human kind which must be preserved and well taken
care for the growth of any country. Plants require intensive care which involves monitoring of …

Reducing the use of agrochemicals is an important component toward sustainable
agriculture. Robots that can perform targeted weed control offer the potential to contribute to …

Selective weeding is one of the key challenges in the field of agriculture robotics. To
accomplish this task, a farm robot should be able to accurately detect plants and to …

Farming robots need a fast and robust image segmentation module to apply targeted
treatments, which require the ability to distinguish, in real time, between crop and weeds …

Farming systems form the backbone of the world food system. The food system, in turn, is a
critical component in sustainable development, with direct linkages to the social, economic …

Semantic segmentation is used in many fields like agriculture, medical imaging, and
autonomous driving. The paper proposes an end to end solution for efficient weeds and crop …

Precision agriculture relies on the availability of accurate knowledge of crop phenotypic
traits at the sub-field level. While visual inspection by human experts has been traditionally …

Based on Unmanned aerial vehicle (UAV) platforms, targeted weed management has
become the mainstream method to address the harm caused by weeds in farmland, and …