17 citations · 20 across the 5 of their papers we have counts for
5 papers
Batch Normalization-Free Fully Integer Quantized Neural Networks via Progressive Tandem Learning
Pengfei Sun, Wenyu Jiang, Piew Yoong Chee +2
Quantised neural networks (QNNs) shrink models and reduce inference energy through low-bit arithmetic, yet most still depend on a running statistics batch normalisation (BN) layer,…
Parallel Delayed Memory Units for Enhanced Temporal Modeling in Biomedical and Bioacoustic Signal Analysis
Pengfei Sun, Wenyu Jiang, Paul Devos +1
Advanced deep learning architectures, particularly recurrent neural networks (RNNs), have been widely applied in audio, bioacoustic, and biomedical signal analysis, especially in d…
EEG decoding with conditional identification information
Pengfei Sun, Jorg De Winne, Paul Devos +1
Decoding EEG signals is crucial for unraveling human brain and advancing brain-computer interfaces. Traditional machine learning algorithms have been hindered by the high noise lev…
Delayed Memory Unit: Modelling Temporal Dependency Through Delay Gate
Pengfei Sun, Jibin Wu, Malu Zhang +2
Recurrent Neural Networks (RNNs) are widely recognized for their proficiency in modeling temporal dependencies, making them highly prevalent in sequential data processing applicati…
Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition
Pengfei Sun, Ehsan Eqlimi, Yansong Chua +2
Spiking neural networks (SNN) are a promising research avenue for building accurate and efficient automatic speech recognition systems. Recent advances in audio-to-spike encoding a…