activity
20172019
most citedCirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices

177 citations · 181 across the 4 of their papers we have counts for

collaborators

12 papers

cs.CV2019

Prior-aware Neural Network for Partially-Supervised Multi-Organ Segmentation

Yuyin Zhou, Zhe Li, Song Bai +5

Accurate multi-organ abdominal CT segmentation is essential to many clinical applications such as computer-aided intervention. As data annotation requires massive human labor from…

cs.CV20191 cited

CircConv: A Structured Convolution with Low Complexity

Siyu Liao, Zhe Li, Liang Zhao +3

Deep neural networks (DNNs), especially deep convolutional neural networks (CNNs), have emerged as the powerful technique in various machine learning applications. However, the lar…

cs.CV20181 cited

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs

Zhe Li, Caiwen Ding, Siyue Wang +8

Recurrent Neural Networks (RNNs) are becoming increasingly important for time series-related applications which require efficient and real-time implementations. The two major types…

cs.NE2018

Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing

Zhe Li, Ji Li, Ao Ren +5

Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success in many machine learning applications. Nevertheless, the deep structure has brought significant i…

cs.LG2018

Learning Topics using Semantic Locality

Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin +4

The topic modeling discovers the latent topic probability of the given text documents. To generate the more meaningful topic that better represents the given document, we proposed…

cs.CV2018

Image Dataset for Visual Objects Classification in 3D Printing

Hongjia Li, Xiaolong Ma, Aditya Singh Rathore +5

The rapid development in additive manufacturing (AM), also known as 3D printing, has brought about potential risk and security issues along with significant benefits. In order to e…