19 citations · 55 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
Security Analysis and Enhancement of Model Compressed Deep Learning Systems under Adversarial Attacks
Qi Liu, Tao Liu, Zihao Liu +3
DNN is presenting human-level performance for many complex intelligent tasks in real-world applications. However, it also introduces ever-increasing security concerns. For example,…
DeepN-JPEG: A Deep Neural Network Favorable JPEG-based Image Compression Framework
Zihao Liu, Tao Liu, Wujie Wen +4
As one of most fascinating machine learning techniques, deep neural network (DNN) has demonstrated excellent performance in various intelligent tasks such as image classification.…
MT-Spike: A Multilayer Time-based Spiking Neuromorphic Architecture with Temporal Error Backpropagation
Tao Liu, Zihao Liu, Fuhong Lin +3
Modern deep learning enabled artificial neural networks, such as Deep Neural Network (DNN) and Convolutional Neural Network (CNN), have achieved a series of breaking records on a b…
PT-Spike: A Precise-Time-Dependent Single Spike Neuromorphic Architecture with Efficient Supervised Learning
Tao Liu, Lei Jiang, Yier Jin +2
One of the most exciting advancements in AI over the last decade is the wide adoption of ANNs, such as DNN and CNN, in many real-world applications. However, the underlying massive…
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples
Zihao Liu, Qi Liu, Tao Liu +4
Image compression-based approaches for defending against the adversarial-example attacks, which threaten the safety use of deep neural networks (DNN), have been investigated recent…