4 citations · 7 across the 16 of their papers we have counts for
17 papers
Hardware-Aware Learned Representation Compression for Distributed In-Sensor Vision
Chengwei Zhou, Abu Masum, Xuming Chen +7
In-sensor computing reduces the cost of transmitting high-resolution image data by performing early-stage processing near the sensor. However, the logic chip integrated with a CMOS…
System-Level Performance Modeling of Photonic In-Memory Computing
Jebacyril Arockiaraj, Sasindu Wijeratne, Sugeet Sunder +4
Photonic in-memory computing is a high-speed, low-energy alternative to traditional transistor-based digital computing that utilizes high photonic operating frequencies and bandwid…
X-pSRAM: A Photonic SRAM with Embedded XOR Logic for Ultra-Fast In-Memory Computing
Md Abdullah-Al Kaiser, Sugeet Sunder, Ajey P. Jacob +1
Traditional von Neumann architectures suffer from fundamental bottlenecks due to continuous data movement between memory and processing units, a challenge that worsens with technol…
A Mixed-Signal Photonic SRAM-based High-Speed Energy-Efficient Photonic Tensor Core with Novel Electro-Optic ADC
Md Abdullah-Al Kaiser, Sugeet Sunder, Ajey P. Jacob +1
The rapid surge in data generated by Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) applications demands ultra-fast, scalable, and energy-efficie…
Design of Energy-Efficient Cross-coupled Differential Photonic-SRAM (pSRAM) Bitcell for High-Speed On-Chip Photonic Memory and Compute Systems
Md Abdullah-Al Kaiser, Sugeet Sunder, Clynn Mathew +3
In this work, we propose a novel differential photonic static random access memory (pSRAM) bitcell design using fabrication-friendly photonic components. The proposed pSRAM overcom…
Predictive Performance of Photonic SRAM-based In-Memory Computing for Tensor Decomposition
Sasindu Wijeratne, Sugeet Sunder, Md Abdullah-Al Kaiser +4
Photonics-based in-memory computing systems have demonstrated a significant speedup over traditional transistor-based systems because of their ultra-fast operating frequencies and…
Voltage-Controlled Magnetic Tunnel Junction based ADC-less Global Shutter Processing-in-Pixel for Extreme-Edge Intelligence
Md Abdullah-Al Kaiser, Gourav Datta, Jordan Athas +5
The vast amount of data generated by camera sensors has prompted the exploration of energy-efficient processing solutions for deploying computer vision tasks on edge devices. Among…
Energy-Efficient & Real-Time Computer Vision with Intelligent Skipping via Reconfigurable CMOS Image Sensors
Md Abdullah-Al Kaiser, Sreetama Sarkar, Peter A. Beerel +2
Current video-based computer vision (CV) applications typically suffer from high energy consumption due to reading and processing all pixels in a frame, regardless of their signifi…
Retina-Inspired Object Motion Segmentation for Event-Cameras
Victoria Clerico, Shay Snyder, Arya Lohia +4
Event-cameras have emerged as a revolutionary technology with a high temporal resolution that far surpasses standard active pixel cameras. This technology draws biological inspirat…
Toward High Performance, Programmable Extreme-Edge Intelligence for Neuromorphic Vision Sensors utilizing Magnetic Domain Wall Motion-based MTJ
Md Abdullah-Al Kaiser, Gourav Datta, Peter A. Beerel +1
The desire to empower resource-limited edge devices with computer vision (CV) must overcome the high energy consumption of collecting and processing vast sensory data. To address t…
Hardware-Algorithm Co-design Enabling Processing-in-Pixel-in-Memory (P2M) for Neuromorphic Vision Sensors
Md Abdullah-Al Kaiser, Akhilesh R. Jaiswal
The high volume of data transmission between the edge sensor and the cloud processor leads to energy and throughput bottlenecks for resource-constrained edge devices focused on com…
Object Motion Sensitivity: A Bio-inspired Solution to the Ego-motion Problem for Event-based Cameras
Shay Snyder, Hunter Thompson, Md Abdullah-Al Kaiser +3
Neuromorphic (event-based) image sensors draw inspiration from the human-retina to create an electronic device that can process visual stimuli in a way that closely resembles its b…
Technology-Circuit-Algorithm Tri-Design for Processing-in-Pixel-in-Memory (P2M)
Md Abdullah-Al Kaiser, Gourav Datta, Sreetama Sarkar +6
The massive amounts of data generated by camera sensors motivate data processing inside pixel arrays, i.e., at the extreme-edge. Several critical developments have fueled recent in…
A Context-Switching/Dual-Context ROM Augmented RAM using Standard 8T SRAM
Md Abdullah-Al Kaiser, Edwin Tieu, Ajey P. Jacob +1
The landscape of emerging applications has been continually widening, encompassing various data-intensive applications like artificial intelligence, machine learning, secure encryp…
Neuromorphic-P2M: Processing-in-Pixel-in-Memory Paradigm for Neuromorphic Image Sensors
Md Abdullah-Al Kaiser, Gourav Datta, Zixu Wang +3
Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-eff…
In-Sensor & Neuromorphic Computing are all you need for Energy Efficient Computer Vision
Gourav Datta, Zeyu Liu, Md Abdullah-Al Kaiser +6
Due to the high activation sparsity and use of accumulates (AC) instead of expensive multiply-and-accumulates (MAC), neuromorphic spiking neural networks (SNNs) have emerged as a p…
IRIS: Integrated Retinal Functionality in Image Sensors
Zihan Yin, Md Abdullah-Al Kaiser, Lamine Ousmane Camara +5
Neuromorphic image sensors draw inspiration from the biological retina to implement visual computations in electronic hardware. Gain control in phototransduction and temporal diffe…