14 citations · 22 across the 15 of their papers we have counts for
16 papers
Adaptive Contrast Enhancement and Optimised Feature Matching for RootSIFT-Based Palm-Vein Recognition
Kaveen Perera, Fouad Khelifi, Ammar Belatreche
Palm-vein recognition is a highly secure biometric modality due to the uniqueness and subcutaneous nature of vein patterns. However, low contrast in palm-vein images, caused by NIR…
TP-Spikformer: Token Pruned Spiking Transformer
Wenjie Wei, Xiaolong Zhou, Malu Zhang +8
Spiking neural networks (SNNs) offer an energy-efficient alternative to traditional neural networks due to their event-driven computing paradigm. However, recent advancements in sp…
Robust Spiking Neural Networks Against Adversarial Attacks
Shuai Wang, Malu Zhang, Yulin Jiang +7
Spiking Neural Networks (SNNs) represent a promising paradigm for energy-efficient neuromorphic computing due to their bio-plausible and spike-driven characteristics. However, the…
BSO: Binary Spiking Online Optimization Algorithm
Yu Liang, Yu Yang, Wenjie Wei +4
Binary Spiking Neural Networks (BSNNs) offer promising efficiency advantages for resource-constrained computing. However, their training algorithms often require substantial memory…
SNN: Sub-bit Spiking Neural Networks
Wenjie Wei, Malu Zhang, Jieyuan Zhang +8
Spiking Neural Networks (SNNs) offer an energy-efficient paradigm for machine intelligence, but their continued scaling poses challenges for resource-limited deployment. Despite re…
Robust Palm-Vein Recognition Using the MMD Filter: Improving SIFT-Based Feature Matching
Kaveen Perera, Fouad Khelifi, Ammar Belatreche
A major challenge with palm vein images is that slight movements of the fingers and thumb, or variations in hand posture, can stretch the skin in different areas and alter the vein…
ILACS-LGOT: A Multi-Layer Contrast Enhancement Approach for Palm-Vein Images
Kaveen Perera, Fouad Khelifi, Ammar Belatreche
This article presents an extended author's version based on our previous work, where we introduced the Multiple Overlapping Tiles (MOT) method for palm vein image enhancement. To b…
Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism
Yu Liang, Wenjie Wei, Ammar Belatreche +5
Binary Spiking Neural Networks (BSNNs) inherit the eventdriven paradigm of SNNs, while also adopting the reduced storage burden of binarization techniques. These distinct advantage…
Spiking Vision Transformer with Saccadic Attention
Shuai Wang, Malu Zhang, Dehao Zhang +7
The combination of Spiking Neural Networks (SNNs) and Vision Transformers (ViTs) holds potential for achieving both energy efficiency and high performance, particularly suitable fo…
QP-SNN: Quantized and Pruned Spiking Neural Networks
Wenjie Wei, Malu Zhang, Zijian Zhou +6
Brain-inspired Spiking Neural Networks (SNNs) leverage sparse spikes to encode information and operate in an asynchronous event-driven manner, offering a highly energy-efficient pa…
Binary Event-Driven Spiking Transformer
Honglin Cao, Zijian Zhou, Wenjie Wei +6
Transformer-based Spiking Neural Networks (SNNs) introduce a novel event-driven self-attention paradigm that combines the high performance of Transformers with the energy efficienc…
Ternary Spike-based Neuromorphic Signal Processing System
Shuai Wang, Dehao Zhang, Ammar Belatreche +5
Deep Neural Networks (DNNs) have been successfully implemented across various signal processing fields, resulting in significant enhancements in performance. However, DNNs generall…
Q-SNNs: Quantized Spiking Neural Networks
Wenjie Wei, Yu Liang, Ammar Belatreche +6
Brain-inspired Spiking Neural Networks (SNNs) leverage sparse spikes to represent information and process them in an asynchronous event-driven manner, offering an energy-efficient…
Event-Driven Learning for Spiking Neural Networks
Wenjie Wei, Malu Zhang, Jilin Zhang +7
Brain-inspired spiking neural networks (SNNs) have gained prominence in the field of neuromorphic computing owing to their low energy consumption during feedforward inference on ne…
Towards Building A Facial Identification System Using Quantum Machine Learning Techniques
Philip Easom-McCaldin, Ahmed Bouridane, Ammar Belatreche +1
In the modern world, facial identification is an extremely important task in which many applications rely on high performing algorithms to detect faces efficiently. Whilst classica…
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…