45 citations · 62 across the 5 of their papers we have counts for
5 papers
LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection
Qiang Chen, Xiangbo Su, Xinyu Zhang +12
In this paper, we present a light-weight detection transformer, LW-DETR, which outperforms YOLOs for real-time object detection. The architecture is a simple stack of a ViT encoder…
MEGA: A Memory-Efficient GNN Accelerator Exploiting Degree-Aware Mixed-Precision Quantization
Zeyu Zhu, Fanrong Li, Gang Li +5
Graph Neural Networks (GNNs) are becoming a promising technique in various domains due to their excellent capabilities in modeling non-Euclidean data. Although a spectrum of accele…
: Aggregation-Aware Quantization for Graph Neural Networks
Zeyu Zhu, Fanrong Li, Zitao Mo +5
As graph data size increases, the vast latency and memory consumption during inference pose a significant challenge to the real-world deployment of Graph Neural Networks (GNNs). Wh…
GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Xingting Yao, Fanrong Li, Zitao Mo +1
Spiking Neural Networks (SNNs) have been studied over decades to incorporate their biological plausibility and leverage their promising energy efficiency. Throughout existing SNNs,…
Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA
Gang Li, Zejian Liu, Fanrong Li +1
Deep convolutional neural networks have achieved remarkable progress in recent years. However, the large volume of intermediate results generated during inference poses a significa…