18 citations · 32 across the 5 of their papers we have counts for
5 papers
From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networks
Xue Geng, Zhe Wang, Chunyun Chen +10
Deep neural networks (DNNs) have been widely used in many artificial intelligence (AI) tasks. However, deploying them brings significant challenges due to the huge cost of memory,…
Efficient Joint Optimization of Layer-Adaptive Weight Pruning in Deep Neural Networks
Kaixin Xu, Zhe Wang, Xue Geng +4
In this paper, we propose a novel layer-adaptive weight-pruning approach for Deep Neural Networks (DNNs) that addresses the challenge of optimizing the output distortion minimizati…
CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flow
Xiuchao Sui, Shaohua Li, Xue Geng +5
Optical flow estimation aims to find the 2D motion field by identifying corresponding pixels between two images. Despite the tremendous progress of deep learning-based optical flow…
Role-Wise Data Augmentation for Knowledge Distillation
Jie Fu, Xue Geng, Zhijian Duan +6
Knowledge Distillation (KD) is a common method for transferring the ``knowledge'' learned by one machine learning model (the \textit{teacher}) into another model (the \textit{stude…
Dataflow-based Joint Quantization of Weights and Activations for Deep Neural Networks
Xue Geng, Jie Fu, Bin Zhao +4
This paper addresses a challenging problem - how to reduce energy consumption without incurring performance drop when deploying deep neural networks (DNNs) at the inference stage.…