12 citations · 32 across the 10 of their papers we have counts for
4 papers · 1 filter
DUSE: A Data Expansion Framework for Low-resource Automatic Modulation Recognition based on Active Learning
Yao Lu, Hongyu Gao, Zhuangzhi Chen +4
Although deep neural networks have made remarkable achievements in the field of automatic modulation recognition (AMR), these models often require a large amount of labeled data fo…
FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition
Yao Lu, Tengfei Ma, Zeyu Wang +5
With the rapid development of wireless communications and the growing complexity of digital modulation schemes, traditional manual modulation recognition methods struggle to extrac…
RGP: Neural Network Pruning through Its Regular Graph Structure
Zhuangzhi Chen, Jingyang Xiang, Yao Lu +2
Lightweight model design has become an important direction in the application of deep learning technology, pruning is an effective mean to achieve a large reduction in model parame…
Adaptive Visibility Graph Neural Network and its Application in Modulation Classification
Qi Xuan, Kunfeng Qiu, Jinchao Zhou +4
Our digital world is full of time series and graphs which capture the various aspects of many complex systems. Traditionally, there are respective methods in processing these two d…