most citedElectroencephalogram Sensor Data Compression Using An Asymmetrical Sparse Autoencoder With A Discrete Cosine Transform Layer

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Discrete Cosine Transform Based Decorrelated Attention for Vision Transformers

Hongyi Pan, Emadeldeen Hamdan, Xin Zhu +2

Self-attention is central to the success of Transformer architectures; however, learning the query, key, and value projections from random initialization remains challenging and co…

eess.IV2024

A Probabilistic Hadamard U-Net for MRI Bias Field Correction

Xin Zhu, Hongyi Pan, Yury Velichko +5

Magnetic field inhomogeneity correction remains a challenging task in MRI analysis. Most established techniques are designed for brain MRI by supposing that image intensities in th…

cs.LG2023

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…

eess.SP20231 cited

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…

eess.SP2023

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…