9 citations · 16 across the 5 of their papers we have counts for
8 papers
An Energy-Efficient Mixed-Signal Parallel Multiply-Accumulate (MAC) Engine Based on Stochastic Computing
Xinyue Zhang, Jiahao Song, Yuan Wang +4
Convolutional neural networks (CNN) have achieved excellent performance on various tasks, but deploying CNN to edge is constrained by the high energy consumption of convolution ope…
Memory System Designed for Multiply-Accumulate (MAC) Engine Based on Stochastic Computing
Xinyue Zhang, Yuan Wang, Yawen Zhang +5
Convolutional neural network (CNN) achieves excellent performance on fascinating tasks such as image recognition and natural language processing at the cost of high power consumpti…
A Parallel Bitstream Generator for Stochastic Computing
Yawen Zhang, Runsheng Wang, Xinyue Zhang +5
Stochastic computing (SC) presents high error tolerance and low hardware cost, and has great potential in applications such as neural networks and image processing. However, the bi…
PointIT: A Fast Tracking Framework Based on 3D Instance Segmentation
Yuan Wang, Yang Yu, Ming Liu
Recently most popular tracking frameworks focus on 2D image sequences. They seldom track the 3D object in point clouds. In this paper, we propose PointIT, a fast, simple tracking m…
A Time Series Graph Cut Image Segmentation Scheme for Liver Tumors
Laramie Paxton, Yufeng Cao, Kevin R. Vixie +3
Tumor detection in biomedical imaging is a time-consuming process for medical professionals and is not without errors. Thus in recent decades, researchers have developed algorithmi…
Focal Loss in 3D Object Detection
Peng Yun, Lei Tai, Yuan Wang +2
3D object detection is still an open problem in autonomous driving scenes. When recognizing and localizing key objects from sparse 3D inputs, autonomous vehicles suffer from a larg…