192 citations · 219 across the 6 of their papers we have counts for
4 papers · 1 filter
Hardware for Machine Learning: Challenges and Opportunities
Vivienne Sze, Yu-Hsin Chen, Joel Emer +2
Machine learning plays a critical role in extracting meaningful information out of the zetabytes of sensor data collected every day. For some applications, the goal is to analyze a…
A 58.6mW Real-Time Programmable Object Detector with Multi-Scale Multi-Object Support Using Deformable Parts Model on 1920x1080 Video at 30fps
Amr Suleiman, Zhengdong Zhang, Vivienne Sze
This paper presents a programmable, energy-efficient and real-time object detection accelerator using deformable parts models (DPM), with 2x higher accuracy than traditional rigid…
FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos
Zhengdong Zhang, Vivienne Sze
State-of-the-art super-resolution (SR) algorithms require significant computational resources to achieve real-time throughput (e.g., 60Mpixels/s for HD video). This paper introduce…
TILT: Transform Invariant Low-rank Textures
Zhengdong Zhang, Arvind Ganesh, Xiao Liang +1
In this paper, we show how to efficiently and effectively extract a class of "low-rank textures" in a 3D scene from 2D images despite significant corruptions and warping. The low-r…