177 citations · 689 across the 74 of their papers we have counts for
6 papers · 1 filter
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation
Geng Yuan, Xiaolong Ma, Sheng Lin +2
The computing wall and data movement challenges of deep neural networks (DNNs) have exposed the limitations of conventional CMOS-based DNN accelerators. Furthermore, the deep struc…
Deep Compressed Pneumonia Detection for Low-Power Embedded Devices
Hongjia Li, Sheng Lin, Ning Liu +2
Deep neural networks (DNNs) have been expanded into medical fields and triggered the revolution of some medical applications by extracting complex features and achieving high accur…
REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs
Caiwen Ding, Shuo Wang, Ning Liu +3
Deep neural networks (DNNs), as the basis of object detection, will play a key role in the development of future autonomous systems with full autonomy. The autonomous systems have…
An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM
Geng Yuan, Xiaolong Ma, Caiwen Ding +7
The high computation and memory storage of large deep neural networks (DNNs) models pose intensive challenges to the conventional Von-Neumann architecture, incurring substantial da…
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…
A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology
Ruizhe Cai, Ao Ren, Olivia Chen +7
The Adiabatic Quantum-Flux-Parametron (AQFP) superconducting technology has been recently developed, which achieves the highest energy efficiency among superconducting logic famili…