26 citations · 82 across the 11 of their papers we have counts for
11 papers
Spiking-LEAF: A Learnable Auditory front-end for Spiking Neural Networks
Zeyang Song, Jibin Wu, Malu Zhang +2
Brain-inspired spiking neural networks (SNNs) have demonstrated great potential for temporal signal processing. However, their performance in speech processing remains limited due…
TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks
Rui-Jie Zhu, Malu Zhang, Qihang Zhao +3
Spiking Neural Networks (SNNs) are attracting widespread interest due to their biological plausibility, energy efficiency, and powerful spatio-temporal information representation a…
Sequential Random Network for Fine-grained Image Classification
Chaorong Li, Malu Zhang, Wei Huang +3
Deep Convolutional Neural Network (DCNN) and Transformer have achieved remarkable successes in image recognition. However, their performance in fine-grained image recognition is st…
Multi-Tones' Phase Coding (MTPC) of Interaural Time Difference by Spiking Neural Network
Zihan Pan, Malu Zhang, Jibin Wu +1
Inspired by the mammal's auditory localization pathway, in this paper we propose a pure spiking neural network (SNN) based computational model for precise sound localization in the…
You Only Spike Once: Improving Energy-Efficient Neuromorphic Inference to ANN-Level Accuracy
Srivatsa P, Kyle Timothy Ng Chu, Burin Amornpaisannon +6
In the past decade, advances in Artificial Neural Networks (ANNs) have allowed them to perform extremely well for a wide range of tasks. In fact, they have reached human parity whe…
Rectified Linear Postsynaptic Potential Function for Backpropagation in Deep Spiking Neural Networks
Malu Zhang, Jiadong Wang, Burin Amornpaisannon +8
Spiking Neural Networks (SNNs) use spatio-temporal spike patterns to represent and transmit information, which is not only biologically realistic but also suitable for ultra-low-po…
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition
Jibin Wu, Emre Yilmaz, Malu Zhang +2
Artificial neural networks (ANN) have become the mainstream acoustic modeling technique for large vocabulary automatic speech recognition (ASR). A conventional ANN features a multi…
Neural Population Coding for Effective Temporal Classification
Zihan Pan, Jibin Wu, Yansong Chua +2
Neural encoding plays an important role in faithfully describing the temporally rich patterns, whose instances include human speech and environmental sounds. For tasks that involve…
An efficient and perceptually motivated auditory neural encoding and decoding algorithm for spiking neural networks
Zihan Pan, Yansong Chua, Jibin Wu +3
Auditory front-end is an integral part of a spiking neural network (SNN) when performing auditory cognitive tasks. It encodes the temporal dynamic stimulus, such as speech and audi…
A Tandem Learning Rule for Effective Training and Rapid Inference of Deep Spiking Neural Networks
Jibin Wu, Yansong Chua, Malu Zhang +3
Spiking neural networks (SNNs) represent the most prominent biologically inspired computing model for neuromorphic computing (NC) architectures. However, due to the non-differentia…
Deep Spiking Neural Network with Spike Count based Learning Rule
Jibin Wu, Yansong Chua, Malu Zhang +3
Deep spiking neural networks (SNNs) support asynchronous event-driven computation, massive parallelism and demonstrate great potential to improve the energy efficiency of its synch…