116 citations · 430 across the 65 of their papers we have counts for
9 papers · 1 filter
CoFi: Coarse-to-Fine ICP for LiDAR Localization in an Efficient Long-lasting Point Cloud Map
Yecheng Lyu, Xinming Huang, Ziming Zhang
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…
Don't Knock! Rowhammer at the Backdoor of DNN Models
M. Caner Tol, Saad Islam, Andrew J. Adiletta +2
State-of-the-art deep neural networks (DNNs) have been proven to be vulnerable to adversarial manipulation and backdoor attacks. Backdoored models deviate from expected behavior on…
Prediction of Metacarpophalangeal joint angles and Classification of Hand configurations based on Ultrasound Imaging of the Forearm
Keshav Bimbraw, Christopher Julius Nycz, Matt Schueler +2
With the advancement in computing and robotics, it is necessary to develop fluent and intuitive methods for interacting with digital systems, AR/VR interfaces, and physical robotic…
LiDAR Odometry Methodologies for Autonomous Driving: A Survey
Nikhil Jonnavithula, Yecheng Lyu, Ziming Zhang
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…
Revisiting 2D Convolutional Neural Networks for Graph-based Applications
Yecheng Lyu, Xinming Huang, Ziming Zhang
Graph convolutional networks (GCNs) are widely used in graph-based applications such as graph classification and segmentation. However, current GCNs have limitations on implementat…
Deep Lucas-Kanade Homography for Multimodal Image Alignment
Yiming Zhao, Xinming Huang, Ziming Zhang
Estimating homography to align image pairs captured by different sensors or image pairs with large appearance changes is an important and general challenge for many computer vision…
A Surface Geometry Model for LiDAR Depth Completion
Yiming Zhao, Lin Bai, Ziming Zhang +1
LiDAR depth completion is a task that predicts depth values for every pixel on the corresponding camera frame, although only sparse LiDAR points are available. Most of the existing…
Training Deep Neural Networks via Branch-and-Bound
Yuanwei Wu, Ziming Zhang, Guanghui Wang
In this paper, we propose BPGrad, a novel approximate algorithm for deep nueral network training, based on adaptive estimates of feasible region via branch-and-bound. The method is…
EllipsoidNet: Ellipsoid Representation for Point Cloud Classification and Segmentation
Yecheng Lyu, Xinming Huang, Ziming Zhang
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 attra…