Search Results for author: Ruisen Luo

Found 5 papers, 0 papers with code

Fully Dense Neural Network for the Automatic Modulation Recognition

no code implementations7 Dec 2019 Miao Du, Qin Yu, Shaomin Fei, Chen Wang, Xiao-Feng Gong, Ruisen Luo

Nowadays, we mainly use various convolution neural network (CNN) structures to extract features from radio data or spectrogram in AMR.

A Radio Signal Modulation Recognition Algorithm Based on Residual Networks and Attention Mechanisms

no code implementations27 Sep 2019 Ruisen Luo, Tao Hu, Zuodong Tang, Chen Wang, Xiaofeng Gong, Haiyan Tu

To solve the problem of inaccurate recognition of types of communication signal modulation, a RNN neural network recognition algorithm combining residual block network with attention mechanism is proposed.

Adaptive Ensemble of Classifiers with Regularization for Imbalanced Data Classification

no code implementations9 Aug 2019 Chen Wang, Chengyuan Deng, Zhoulu Yu, Dafeng Hui, Xiaofeng Gong, Ruisen Luo

In addition, the proposed method has other preferred properties such as special advantages in dealing with highly imbalanced data, and it pioneers the research on the regularization for dynamic ensemble methods.

Classification General Classification

Multi-layer Attention Mechanism for Speech Keyword Recognition

no code implementations10 Jul 2019 Ruisen Luo, Tianran Sun, Chen Wang, Miao Du, Zuodong Tang, Kai Zhou, Xiao-Feng Gong, Xiaomei Yang

The key idea is that, in addition to the conventional attention mechanism, information of layers prior to feature extraction and LSTM are introduced into attention weights calculations.

Ranked #4 on Keyword Spotting on Google Speech Commands (Google Speech Commands V2 20 metric)

Keyword Spotting speech-recognition +1

Scalar Quantization as Sparse Least Square Optimization

no code implementations1 Mar 2018 Chen Wang, Xiaomei Yang, Shaomin Fei, Kai Zhou, Xiao-Feng Gong, Miao Du, Ruisen Luo

Furthermore, to compute quantization results with a given amount of values/clusters, this paper designed an iterative method and a clustering-based method, and both of them are built on sparse least square.


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