21 citations · 33 across the 11 of their papers we have counts for
4 papers · 1 filter
Towards Understanding the Effect of Leak in Spiking Neural Networks
Sayeed Shafayet Chowdhury, Chankyu Lee, Kaushik Roy
Spiking Neural Networks (SNNs) are being explored to emulate the astounding capabilities of human brain that can learn and compute functions robustly and efficiently with noisy spi…
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
Chankyu Lee, Adarsh Kumar Kosta, Alex Zihao Zhu +3
Event-based cameras display great potential for a variety of tasks such as high-speed motion detection and navigation in low-light environments where conventional frame-based camer…
A Comprehensive Analysis on Adversarial Robustness of Spiking Neural Networks
Saima Sharmin, Priyadarshini Panda, Syed Shakib Sarwar +3
In this era of machine learning models, their functionality is being threatened by adversarial attacks. In the face of this struggle for making artificial neural networks robust, f…
Enabling Spike-based Backpropagation for Training Deep Neural Network Architectures
Chankyu Lee, Syed Shakib Sarwar, Priyadarshini Panda +2
Spiking Neural Networks (SNNs) have recently emerged as a prominent neural computing paradigm. However, the typical shallow SNN architectures have limited capacity for expressing c…