7 citations · 7 across the 2 of their papers we have counts for
5 papers
On the Intrinsic Robustness of NVM Crossbars Against Adversarial Attacks
Deboleena Roy, Indranil Chakraborty, Timur Ibrayev +1
The increasing computational demand of Deep Learning has propelled research in special-purpose inference accelerators based on emerging non-volatile memory (NVM) technologies. Such…
Constructing Energy-efficient Mixed-precision Neural Networks through Principal Component Analysis for Edge Intelligence
Indranil Chakraborty, Deboleena Roy, Isha Garg +2
The `Internet of Things' has brought increased demand for AI-based edge computing in applications ranging from healthcare monitoring systems to autonomous vehicles. Quantization is…
Synthesizing Images from Spatio-Temporal Representations using Spike-based Backpropagation
Deboleena Roy, Priyadarshini Panda, Kaushik Roy
Spiking neural networks (SNNs) offer a promising alternative to current artificial neural networks to enable low-power event-driven neuromorphic hardware. Spike-based neuromorphic…
Efficient Hybrid Network Architectures for Extremely Quantized Neural Networks Enabling Intelligence at the Edge
Indranil Chakraborty, Deboleena Roy, Aayush Ankit +1
The recent advent of `Internet of Things' (IOT) has increased the demand for enabling AI-based edge computing. This has necessitated the search for efficient implementations of neu…
Xcel-RAM: Accelerating Binary Neural Networks in High-Throughput SRAM Compute Arrays
Amogh Agrawal, Akhilesh Jaiswal, Deboleena Roy +4
Deep neural networks are a biologically-inspired class of algorithms that have recently demonstrated state-of-the-art accuracies involving large-scale classification and recognitio…