440 citations · 680 across the 14 of their papers we have counts for
14 papers
x-RAGE: eXtended Reality -- Action & Gesture Events Dataset
Vivek Parmar, Dwijay Bane, Syed Shakib Sarwar +3
With the emergence of the Metaverse and focus on wearable devices in the recent years gesture based human-computer interaction has gained significance. To enable gesture recognitio…
PETAH: Parameter Efficient Task Adaptation for Hybrid Transformers in a resource-limited Context
Maximilian Augustin, Syed Shakib Sarwar, Mostafa Elhoushi +3
Following their success in natural language processing (NLP), there has been a shift towards transformer models in computer vision. While transformers perform well and offer promis…
Siracusa: A 16 nm Heterogenous RISC-V SoC for Extended Reality with At-MRAM Neural Engine
Arpan Suravi Prasad, Moritz Scherer, Francesco Conti +9
Extended reality (XR) applications are Machine Learning (ML)-intensive, featuring deep neural networks (DNNs) with millions of weights, tightly latency-bound (10-20 ms end-to-end),…
DRESS: Dynamic REal-time Sparse Subnets
Zhongnan Qu, Syed Shakib Sarwar, Xin Dong +3
The limited and dynamically varied resources on edge devices motivate us to deploy an optimized deep neural network that can adapt its sub-networks to fit in different resource con…
Memory-Oriented Design-Space Exploration of Edge-AI Hardware for XR Applications
Vivek Parmar, Syed Shakib Sarwar, Ziyun Li +3
Low-Power Edge-AI capabilities are essential for on-device extended reality (XR) applications to support the vision of Metaverse. In this work, we investigate two representative XR…
Distributed On-Sensor Compute System for AR/VR Devices: A Semi-Analytical Simulation Framework for Power Estimation
Jorge Gomez, Saavan Patel, Syed Shakib Sarwar +8
Augmented Reality/Virtual Reality (AR/VR) glasses are widely foreseen as the next generation computing platform. AR/VR glasses are a complex "system of systems" which must satisfy…
Power-of-Two Quantization for Low Bitwidth and Hardware Compliant Neural Networks
Dominika Przewlocka-Rus, Syed Shakib Sarwar, H. Ekin Sumbul +2
Deploying Deep Neural Networks in low-power embedded devices for real time-constrained applications requires optimization of memory and computational complexity of the networks, us…
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…
Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing
Syed Shakib Sarwar, Aayush Ankit, Kaushik Roy
Deep convolutional neural network (DCNN) based supervised learning is a widely practiced approach for large-scale image classification. However, retraining these large networks to…
Gabor Filter Assisted Energy Efficient Fast Learning Convolutional Neural Networks
Syed Shakib Sarwar, Priyadarshini Panda, Kaushik Roy
Convolutional Neural Networks (CNN) are being increasingly used in computer vision for a wide range of classification and recognition problems. However, training these large networ…
Multiplier-less Artificial Neurons Exploiting Error Resiliency for Energy-Efficient Neural Computing
Syed Shakib Sarwar, Swagath Venkataramani, Anand Raghunathan +1
Large-scale artificial neural networks have shown significant promise in addressing a wide range of classification and recognition applications. However, their large computational…
Significance Driven Hybrid 8T-6T SRAM for Energy-Efficient Synaptic Storage in Artificial Neural Networks
Gopalakrishnan Srinivasan, Parami Wijesinghe, Syed Shakib Sarwar +2
Multilayered artificial neural networks (ANN) have found widespread utility in classification and recognition applications. The scale and complexity of such networks together with…
Spin-Torque Sensors for Energy Efficient High Speed Long Interconnects
Zubair Al Azim, Abhronil Sengupta, Syed Shakib Sarwar +1
In this paper, we propose a Spin-Torque (ST) based sensing scheme that can enable energy efficient multi-bit long distance interconnect architectures. Current-mode interconnects ha…