7 citations · 29 across the 22 of their papers we have counts for
9 papers · 1 filter
A novel asymmetrical autoencoder with a sparsifying discrete cosine Stockwell transform layer for gearbox sensor data compression
Xin Zhu, Daoguang Yang, Hongyi Pan +3
The lack of an efficient compression model remains a challenge for the wireless transmission of gearbox data in non-contact gear fault diagnosis problems. In this paper, we present…
Electroencephalogram Sensor Data Compression Using An Asymmetrical Sparse Autoencoder With A Discrete Cosine Transform Layer
Xin Zhu, Hongyi Pan, Shuaiang Rong +1
Electroencephalogram (EEG) data compression is necessary for wireless recording applications to reduce the amount of data that needs to be transmitted. In this paper, an asymmetric…
ADC/DAC-Free Analog Acceleration of Deep Neural Networks with Frequency Transformation
Nastaran Darabi, Maeesha Binte Hashem, Hongyi Pan +3
The edge processing of deep neural networks (DNNs) is becoming increasingly important due to its ability to extract valuable information directly at the data source to minimize lat…
Domain Generalization with Fourier Transform and Soft Thresholding
Hongyi Pan, Bin Wang, Zheyuan Zhang +5
Domain generalization aims to train models on multiple source domains so that they can generalize well to unseen target domains. Among many domain generalization methods, Fourier-t…
Stein Variational Gradient Descent-based Detection For Random Access With Preambles In MTC
Xin Zhu, Hongyi Pan, Salih Atici +1
Traditional preamble detection algorithms have low accuracy in the grant-based random access scheme in massive machine-type communication (mMTC). We present a novel preamble detect…
Wildfire Detection Via Transfer Learning: A Survey
Ziliang Hong, Emadeldeen Hamdan, Yifei Zhao +3
This paper surveys different publicly available neural network models used for detecting wildfires using regular visible-range cameras which are placed on hilltops or forest lookou…
GazeGNN: A Gaze-Guided Graph Neural Network for Chest X-ray Classification
Bin Wang, Hongyi Pan, Armstrong Aboah +7
Eye tracking research is important in computer vision because it can help us understand how humans interact with the visual world. Specifically for high-risk applications, such as…
A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer
Hongyi Pan, Xin Zhu, Salih Atici +1
In this paper, we propose a novel Hadamard Transform (HT)-based neural network layer for hybrid quantum-classical computing. It implements the regular convolutional layers in the H…
Multichannel Orthogonal Transform-Based Perceptron Layers for Efficient ResNets
Hongyi Pan, Emadeldeen Hamdan, Xin Zhu +2
In this paper, we propose a set of transform-based neural network layers as an alternative to the Conv2D layers in Convolutional Neural Networks (CNNs). The proposed lay…