Publications (9)
PISA: A Binary-Weight Processing-In-Sensor Accelerator for Edge Image Processing
Shaahin Angizi, Sepehr Tabrizchi, Arman Roohi
This work proposes a Processing-In-Sensor Accelerator, namely PISA, as a flexible, energy-efficient, and high-performance solution for real-time and smart image processing in AI de…
DIAC: Design Exploration of Intermittent-Aware Computing Realizing Batteryless Systems
Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi
Battery-powered IoT devices face challenges like cost, maintenance, and environmental sustainability, prompting the emergence of batteryless energy-harvesting systems that harness…
A Near-Sensor Processing Accelerator for Approximate Local Binary Pattern Networks
Shaahin Angizi, Mehrdad Morsali, Sepehr Tabrizchi +1
In this work, a high-speed and energy-efficient comparator-based Near-Sensor Local Binary Pattern accelerator architecture (NS-LBP) is proposed to execute a novel local binary patt…
OISA: Architecting an Optical In-Sensor Accelerator for Efficient Visual Computing
Mehrdad Morsali, Sepehr Tabrizchi, Deniz Najafi +4
Targeting vision applications at the edge, in this work, we systematically explore and propose a high-performance and energy-efficient Optical In-Sensor Accelerator architecture ca…
Lightator: An Optical Near-Sensor Accelerator with Compressive Acquisition Enabling Versatile Image Processing
Mehrdad Morsali, Brendan Reidy, Deniz Najafi +6
This paper proposes a high-performance and energy-efficient optical near-sensor accelerator for vision applications, called Lightator. Harnessing the promising efficiency offered b…
NeSe: Near-Sensor Event-Driven Scheme for Low Power Energy Harvesting Sensors
Sepehr Tabrizchi, Mehrdad Morsali, Shaahin Angizi +1
Digital technologies have made it possible to deploy visual sensor nodes capable of detecting motion events in the coverage area cost-effectively. However, background subtraction,…
HiRISE: High-Resolution Image Scaling for Edge ML via In-Sensor Compression and Selective ROI
Brendan Reidy, Sepehr Tabrizchi, Mohamadreza Mohammadi +3
With the rise of tiny IoT devices powered by machine learning (ML), many researchers have directed their focus toward compressing models to fit on tiny edge devices. Recent works h…
GLANCE: Gaze-Led Attention Network for Compressed Edge-inference
Neeraj Solanki, Hong Ding, Sepehr Tabrizchi +4
Real-time object detection in AR/VR systems faces critical computational constraints, requiring sub-10\,ms latency within tight power budgets. Inspired by biological foveal vision,…
ATM-Net: Adaptive Termination and Multi-Precision Neural Networks for Energy-Harvested Edge Intelligence
Neeraj Solanki, Sepehr Tabrizchi, Samin Sohrabi +2
ATM-Net is a novel neural network architecture tailored for energy-harvested IoT devices, integrating adaptive termination points with multi-precision computing. It dynamically adj…