activity
20172020
most citedA Unified Hardware Architecture for Convolutions and Deconvolutions in CNN

5 citations · 8 across the 4 of their papers we have counts for

collaborators

5 papers

eess.IV20201 cited

DepthNet: Real-Time LiDAR Point Cloud Depth Completion for Autonomous Vehicles

Lin Bai, Yiming Zhao, Mahdi Elhousni +1

Autonomous vehicles rely heavily on sensors such as camera and LiDAR, which provide real-time information about their surroundings for the tasks of perception, planning and control…

eess.SP20205 cited

A Unified Hardware Architecture for Convolutions and Deconvolutions in CNN

Lin Bai, Yecheng Lyu, Xinming Huang

In this paper, a scalable neural network hardware architecture for image segmentation is proposed. By sharing the same computing resources, both convolution and deconvolution opera…

eess.SP20201 cited

PointNet on FPGA for Real-Time LiDAR Point Cloud Processing

Lin Bai, Yecheng Lyu, Xin Xu +1

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 f…

eess.IV2019

An Interactive LiDAR to Camera Calibration

Yecheng Lyu, Lin Bai, Mahdi Elhousni +1

Recent progress in the automated driving system (ADS) and advanced driver assistant system (ADAS) has shown that the combined use of 3D light detection and ranging (LiDAR) and the…

cs.RO20171 cited

Real-Time Road Segmentation Using LiDAR Data Processing on an FPGA

Yecheng Lyu, Lin Bai, Xinming Huang

This paper presents the FPGA design of a convolutional neural network (CNN) based road segmentation algorithm for real-time processing of LiDAR data. For autonomous vehicles, it is…