During automated driving in urban areas, decisions must be made while recognizing the
surrounding environment using sensors such as camera, Light Detection and Ranging …

Managing, processing and understanding big healthcare data is challenging, costly and
demanding. Without a robust fundamental theory for representation, analysis and inference …

Siamese network based trackers formulate 3D single object tracking as cross-correlation
learning between point features of a template and a search area. Due to the large …

Abstract 3D object tracking in point clouds is still a challenging problem due to the sparsity of
LiDAR points in dynamic environments. In this work, we propose a Siamese voxel-to-BEV …

Point clouds are challenging to process due to their sparsity, therefore autonomous vehicles
rely more on appearance attributes than pure geometric features. However, 3D LIDAR …

This paper studies the pedestrian recognition and tracking problem for autonomous vehicles
using a 3D LiDAR, a classifier trained by SVM (Support Vector Machine) is used to …

Background Microbial inhabitants of soils are important to ecosystem and planetary
functions, yet there are large gaps in our knowledge of their diversity and ecology. The …

Abstract 3D single object tracking plays an essential role in many applications, such as
autonomous driving. It remains a challenging problem due to the large appearance variation …

Robots are expected to operate autonomously in increasingly complex scenarios such as
crowded streets or heavy traffic situations. Perceiving the dynamics of moving objects in the …

Abstract 3D single object tracking has been a crucial problem for decades with numerous
applications such as autonomous driving. Despite its wide-ranging use, this task remains …