Chenzhuo Zhu — accepted AI-conference papers

2017

Shape-independent hardness estimation using deep learning and a GelSight tactile sensor

Wenzhen Yuan, Chenzhuo Zhu, Andrew Owens, Mandayam A. Srinivasan, Edward H. Adelson

ICRA 2017poster

Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack of information provided by current tactile sensors. In this work, we address these limitations by introducing a novel m…

Cited by 223 Source ↗Scholar ↗

2017

Trained Ternary Quantization

Chenzhuo Zhu, Song Han, Huizi Mao, William J. Dally

ICLR 2017poster

Deep neural networks are widely used in machine learning applications. However, the deployment of large neural networks models can be difficult to deploy on mobile devices with limited power budgets. To solve this problem, we propose Trained Ternary Quantization (TTQ), a method that can reduce the p…

Cited by 1391 Source ↗Scholar ↗