In the past decade, deep neural networks, particularly convolutional neural networks, have
revolutionised computer vision. However, all deep learning models may require a large …

Perception in autonomous vehicles is often carried out through a suite of different sensing
modalities. Given the massive amount of openly available labeled RGB data and the advent …

Weeds are a significant threat to agricultural productivity and the environment. The
increasing demand for sustainable weed control practices has driven innovative …

Artificial perception for robots operating in outdoor natural environments, including forest
scenarios, has been the object of a substantial amount of research for decades. Regardless …

Localization and mapping are key capabilities of autonomous systems. In this paper, we
propose a modified Siamese network to estimate the similarity between pairs of LiDAR …

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

Precision herbicide application can substantially reduce herbicide input and weed control
cost in turfgrass management systems. Intelligent spot-spraying system predominantly relies …

Semantic perception is a core building block in autonomous driving, since it provides
information about the drivable space and location of other traffic participants. For learning …

Precision agriculture is gaining increasing attention because of the possible reduction of
agricultural inputs (eg, fertilizers and pesticides) that can be obtained by using hightech …

The extraction of phenotypic traits is often very time and labour intensive. Especially the
investigation in viticulture is restricted to an on-site analysis due to the perennial nature of …