Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Lyu, Yecheng"'
LiDAR odometry and localization has attracted increasing research interest in recent years. In the existing works, iterative closest point (ICP) is widely used since it is precise and efficient. Due to its non-convexity and its local iterative strate
Externí odkaz:
http://arxiv.org/abs/2110.10194
Vehicle odometry is an essential component of an automated driving system as it computes the vehicle's position and orientation. The odometry module has a higher demand and impact in urban areas where the global navigation satellite system (GNSS) sig
Externí odkaz:
http://arxiv.org/abs/2109.06120
Graph convolutional networks (GCNs) are widely used in graph-based applications such as graph classification and segmentation. However, current GCNs have limitations on implementation such as network architectures due to their irregular inputs. In co
Externí odkaz:
http://arxiv.org/abs/2105.11016
Point cloud patterns are hard to learn because of the implicit local geometry features among the orderless points. In recent years, point cloud representation in 2D space has attracted increasing research interest since it exposes the local geometry
Externí odkaz:
http://arxiv.org/abs/2103.02517
Deep learning based LiDAR odometry (LO) estimation attracts increasing research interests in the field of autonomous driving and robotics. Existing works feed consecutive LiDAR frames into neural networks as point clouds and match pairs in the learne
Externí odkaz:
http://arxiv.org/abs/2009.00164
General graphs are difficult for learning due to their irregular structures. Existing works employ message passing along graph edges to extract local patterns using customized graph kernels, but few of them are effective for the integration of such l
Externí odkaz:
http://arxiv.org/abs/2006.11825
Publikováno v:
in IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 68, no. 2, pp. 704-714, Feb. 2021
In recent years, convolutional neural network has gained popularity in many engineering applications especially for computer vision. In order to achieve better performance, often more complex structures and advanced operations are incorporated into t
Externí odkaz:
http://arxiv.org/abs/2006.07644
In a world where autonomous driving cars are becoming increasingly more common, creating an adequate infrastructure for this new technology is essential. This includes building and labeling high-definition (HD) maps accurately and efficiently. Today,
Externí odkaz:
http://arxiv.org/abs/2006.00644
LiDAR sensors have been widely used in many autonomous vehicle modalities, such as perception, mapping, and localization. This paper presents an FPGA-based deep learning platform for real-time point cloud processing targeted on autonomous vehicles. T
Externí odkaz:
http://arxiv.org/abs/2006.00049
In this paper, a scalable neural network hardware architecture for image segmentation is proposed. By sharing the same computing resources, both convolution and deconvolution operations are handled by the same process element array. In addition, acce
Externí odkaz:
http://arxiv.org/abs/2006.00053