35 citations · 84 across the 10 of their papers we have counts for
4 papers · 1 filter
BlissCam: Boosting Eye Tracking Efficiency with Learned In-Sensor Sparse Sampling
Yu Feng, Tianrui Ma, Yuhao Zhu +1
Eye tracking is becoming an increasingly important task domain in emerging computing platforms such as Augmented/Virtual Reality (AR/VR). Today's eye tracking system suffers from l…
Characterizing Soft-Error Resiliency in Arm's Ethos-U55 Embedded Machine Learning Accelerator
Abhishek Tyagi, Reiley Jeyapaul, Chuteng Zhu +2
As Neural Processing Units (NPU) or accelerators are increasingly deployed in a variety of applications including safety critical applications such as autonomous vehicle, and medic…
Crescent: Taming Memory Irregularities for Accelerating Deep Point Cloud Analytics
Yu Feng, Gunnar Hammonds, Yiming Gan +1
3D perception in point clouds is transforming the perception ability of future intelligent machines. Point cloud algorithms, however, are plagued by irregular memory accesses, lead…
S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration
Zhi-Gang Liu, Paul N. Whatmough, Yuhao Zhu +1
Exploiting sparsity is a key technique in accelerating quantized convolutional neural network (CNN) inference on mobile devices. Prior sparse CNN accelerators largely exploit un-st…