The task of semantic segmentation holds a fundamental position in the field of computer
vision. Assigning a semantic label to each pixel in an image is a challenging task. In recent …

The incorporation of physical information in machine learning frameworks is opening and
transforming many application domains. Here the learning process is augmented through …

With the rise in popularity of autonomous driving, the speed and accuracy of surrounding
objects' detection by in-vehicle sensing technology is becoming increasingly important for …

With the rapid development of deep learning in recent years, the level of automatic driving
perception has also increased substantially. However, automatic driving perception under …

Semantic segmentation of cityscapes via deep learning is an essential and game-changing
research topic that offers a more nuanced comprehension of urban landscapes. Deep …

Global navigation satellite system (GNSS) signals cannot be received indoors, thus to
deploy intelligent vehicles in underground car parks other localization methods are needed …

Accurately predicting the trajectory of road agents in complex traffic scenarios is challenging
because the movement patterns of agents are complex and stochastic, not only depending …

In recent years, the advancement of deep-learning technologies has greatly promoted the
research progress of autonomous driving. However, deep neural network is like a black box …

Enhancing the accuracy and reliability of perception systems in automated vehicles is
critical, especially under varying driving conditions. Unfortunately, the challenges of adverse …

A sideslip angle fusion estimation strategy of the three-axis vehicle based on an adaptive
cubature Kalman filter (ACKF) is investigated in this article. According to the dynamics …