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20122021
most citedGabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks

79 citations · 495 across the 38 of their papers we have counts for

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7 papers · 1 filter

cs.CV20211 cited

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

Chankyu Lee, Adarsh Kumar Kosta, Kaushik Roy

Standard frame-based cameras that sample light intensity frames are heavily impacted by motion blur for high-speed motion and fail to perceive scene accurately when the dynamic ran…

cs.CV2020

Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations

Saima Sharmin, Nitin Rathi, Priyadarshini Panda +1

In the recent quest for trustworthy neural networks, we present Spiking Neural Network (SNN) as a potential candidate for inherent robustness against adversarial attacks. In this w…

cs.CV20197 cited

Towards Scalable, Efficient and Accurate Deep Spiking Neural Networks with Backward Residual Connections, Stochastic Softmax and Hybridization

Priyadarshini Panda, Aparna Aketi, Kaushik Roy

Spiking Neural Networks (SNNs) may offer an energy-efficient alternative for implementing deep learning applications. In recent years, there have been several proposals focused on…

cs.CV20193 cited

ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing

Gopalakrishnan Srinivasan, Kaushik Roy

In this work, we propose ReStoCNet, a residual stochastic multilayer convolutional Spiking Neural Network (SNN) composed of binary kernels, to reduce the synaptic memory footprint…

cs.CV2018

A Low Effort Approach to Structured CNN Design Using PCA

Isha Garg, Priyadarshini Panda, Kaushik Roy

Deep learning models hold state of the art performance in many fields, yet their design is still based on heuristics or grid search methods that often result in overparametrized ne…

cs.CV2018

Tree-CNN: A Hierarchical Deep Convolutional Neural Network for Incremental Learning

Deboleena Roy, Priyadarshini Panda, Kaushik Roy

Over the past decade, Deep Convolutional Neural Networks (DCNNs) have shown remarkable performance in most computer vision tasks. These tasks traditionally use a fixed dataset, and…