9 citations · 22 across the 8 of their papers we have counts for
10 papers
WeConvene: Learned Image Compression with Wavelet-Domain Convolution and Entropy Model
Haisheng Fu, Jie Liang, Zhenman Fang +3
Recently learned image compression (LIC) has achieved great progress and even outperformed the traditional approach using DCT or discrete wavelet transform (DWT). However, LIC main…
Learned Image Compression with Dual-Branch Encoder and Conditional Information Coding
Haisheng Fu, Feng Liang, Jie Liang +3
Recent advancements in deep learning-based image compression are notable. However, prevalent schemes that employ a serial context-adaptive entropy model to enhance rate-distortion…
A Cycle-Accurate Soft Error Vulnerability Analysis Framework for FPGA-based Designs
Eduardo Rhod, Behnam Ghavami, Zhenman Fang +1
Many aerospace and automotive applications use FPGAs in their designs due to their low power and reconfigurability requirements. Meanwhile, such applications also pose a high stand…
SASA: A Scalable and Automatic Stencil Acceleration Framework for Optimized Hybrid Spatial and Temporal Parallelism on HBM-based FPGAs
Xingyu Tian, Zhifan Ye, Alec Lu +3
Stencil computation is one of the fundamental computing patterns in many application domains such as scientific computing and image processing. While there are promising studies th…
Auto-ViT-Acc: An FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization
Zhengang Li, Mengshu Sun, Alec Lu +9
Vision transformers (ViTs) are emerging with significantly improved accuracy in computer vision tasks. However, their complex architecture and enormous computation/storage demand i…
FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions
Behnam Ghavami, Mani Sadati, Zhenman Fang +1
Deep neural networks (DNNs) are increasingly being deployed in safety-critical systems such as personal healthcare devices and self-driving cars. In such DNN-based systems, error r…