Building Information models created from laser scanning inputs are becoming increasingly
commonplace, but the automation of the modeling and evaluation is still a subject of …

The semantic segmentation of small objects in point clouds is currently one of the most
demanding tasks in photogrammetry and remote sensing applications. Multi-resolution …

The increasing use of deep learning techniques has reduced interpretation time and, ideally,
reduced interpreter bias by automatically deriving geological maps from digital outcrop …

In this paper, we propose a deep learning-based perception method in autonomous driving
systems using a Light Detection and Ranging (LiDAR) point cloud data, which is called a …

LiDAR sensors can provide dependable 3D spatial information at a low frequency (around
10 Hz) and have been widely applied in the field of autonomous driving and unmanned …

Deep learning is robust to the perturbation of a point cloud, which is an important data form
in the Internet of Things. However, it cannot effectively capture the local information of the …

Whereas MDD is characterized in part by changes in mood, other symptoms can also cause
significant impairment, including sexual dysfunction, cognitive impairment, and fatigue …

In the semantic segmentation of a point cloud, if the spatial structure correlation between the
input features and coordinates are not fully considered, a semantic segmentation error can …

点云数据蕴含丰富的空间信息, 可以通过激光雷达, 3D 传感器等设备大量采集,
被广泛应用于自动驾驶, 虚拟现实, 城市规划和3D 重建等领域. 点云语义分割作为3D 场景理解 …

摘要2D 激光雷达成本较低, 抗干扰性强, 在行人检测中被广泛使用, 但由于其点云信息的无序
稀疏性, 给行人检测问题带来了许多挑战. 针对上述问题, 提出一种点云与图像的转换模型 …