Publications

Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures

Standard frame-based cameras that sample light intensity frames are heavily impacted by motion blur for high-speed motion and fail to …
Chankyu Lee, Adarsh Kosta, Kaushik Roy. IEEE International Conference on Robotics and Automation (ICRA), 2022
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Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures

Towards Understanding the Effect of Leak in Spiking Neural Networks

Spiking Neural Networks (SNNs) are being explored to emulate the astounding capabilities of human brain that can learn and compute …
Sayeed Shafayet Chowdhury*, Chankyu Lee*, Kaushik Roy (*Equal Contribution). Neurocomputing, 2021
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Towards Understanding the Effect of Leak in Spiking Neural Networks

Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks

Event-based cameras display great potential for a variety of conditions such as high-speed motion detection and enabling navigation in …
Chankyu Lee, Adarsh Kosta, Alex Zihao Zhu, Kenneth Chaney, Kostas Daniilidis, Kaushik Roy. In Proceedings of the European Conference on Computer Vision (ECCV) 2020
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Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks

Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures

Spiking Neural Networks (SNNs) have recently emerged as a prominent neural computing paradigm. However, the typical shallow SNN …
Chankyu Lee*, Syed Shakib Sarwar*, Priyadarshini Panda, Gopalakrishnan Srinivasan, Kaushik Roy (*Equal Contribution). Frontiers in Neuroscience, Neuromorphic Engineering, 2020
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Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures

Training Deep Spiking Convolutional Neural Networks with STDP-based Unsupervised Pre-training Followed by Supervised Fine-tuning

Spiking Neural Networks (SNNs) are fast becoming a promising candidate for brain-inspired neuromorphic computing because of their …
Chankyu Lee, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy. Frontiers in Neuroscience, Neuromorphic Engineering, 2018
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Training Deep Spiking Convolutional Neural Networks with STDP-based Unsupervised Pre-training Followed by Supervised Fine-tuning

Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity

Spiking neural networks (SNNs) have emerged as a promising brain inspired neuromorphic-computing paradigm for cognitive system design …
Chankyu Lee, Gopalakrishnan Srinivasan, Priyadarshini Panda, Kaushik Roy. IEEE Transactions on Cognitive and Developmental Systems (TCDS), 2018
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Deep Spiking Convolutional Neural Network Trained With Unsupervised Spike-Timing-Dependent Plasticity