activity
20162022
most citedProgressive DNN Compression: A Key to Achieve Ultra-High Weight Pruning and Quantization Rates using ADMM

26 citations · 50 across the 7 of their papers we have counts for

collaborators

18 papers

cs.CR20226 cited

CryptoGCN: Fast and Scalable Homomorphically Encrypted Graph Convolutional Network Inference

Ran Ran, Nuo Xu, Wei Wang +3

Recently cloud-based graph convolutional network (GCN) has demonstrated great success and potential in many privacy-sensitive applications such as personal healthcare and financial…

cs.CV20205 cited

Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device

Pu Zhao, Wei Niu, Geng Yuan +7

3D object detection is an important task, especially in the autonomous driving application domain. However, it is challenging to support the real-time performance with the limited…

eess.IV20201 cited

Do Noises Bother Human and Neural Networks In the Same Way? A Medical Image Analysis Perspective

Shao-Cheng Wen, Yu-Jen Chen, Zihao Liu +7

Deep learning had already demonstrated its power in medical images, including denoising, classification, segmentation, etc. All these applications are proposed to automatically ana…

eess.SP2019

Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation

Xiaolong Ma, Geng Yuan, Sheng Lin +6

The state-of-art DNN structures involve intensive computation and high memory storage. To mitigate the challenges, the memristor crossbar array has emerged as an intrinsically suit…

cs.AR2019

Thread Batching for High-performance Energy-efficient GPU Memory Design

Bing Li, Mengjie Mao, Xiaoxiao Liu +6

Massive multi-threading in GPU imposes tremendous pressure on memory subsystems. Due to rapid growth in thread-level parallelism of GPU and slowly improved peak memory bandwidth, t…

cs.CV201911 cited

Machine Vision Guided 3D Medical Image Compression for Efficient Transmission and Accurate Segmentation in the Clouds

Zihao Liu, Xiaowei Xu, Tao Liu +7

Cloud based medical image analysis has become popular recently due to the high computation complexities of various deep neural network (DNN) based frameworks and the increasingly l…