Related papers: Transporter: A 128$\times$4 SPAD Imager with On-ch…
Neuromorphic computing, inspired by the functionality and efficiency of biological neural systems, holds promise for advancing artificial intelligence and computational paradigms. Resonant tunneling diodes (RTDs), thanks to their ability to…
Single-photon avalanche diodes (SPADs) are an emerging sensor technology capable of detecting individual incident photons, and capturing their time-of-arrival with high timing precision. While these sensors were limited to single-pixel or…
Current state-of-the-art methods of image classification using convolutional neural networks are often constrained by both latency and power consumption. This places a limit on the devices, particularly low-power edge devices, that can…
In this work, we introduce an optoelectronic spiking artificial neuron capable of operating at ultrafast rates ($\approx$ 100 ps/optical spike) and with low energy consumption ($<$ pJ/spike). The proposed system combines an excitable…
Recently, large models, such as Vision Transformer and BERT, have garnered significant attention due to their exceptional performance. However, their extensive computational requirements lead to considerable power and hardware resource…
Spike-based encoders represent information as sequences of spikes or pulses, which are transmitted between neurons. A prevailing consensus suggests that spike-based approaches demonstrate exceptional capabilities in capturing the temporal…
Single-photon avalanche diodes (SPADs) are advanced sensors capable of detecting individual photons and recording their arrival times with picosecond resolution using time-correlated Single-Photon Counting detection techniques. They are…
Single-photon avalanche diode (SPAD) based transient imaging suffers from an aberration called pile-up. When multiple photons arrive within a single repetition period of the illuminating laser, the SPAD records only the arrival of the first…
Single-photon avalanche diode (SPAD) arrays are solid-state detectors offering imaging capabilities at the level of individual photons, with unparalleled photon counting and time-resolved performance. This fascinating technology has…
A near-infrared (NIR) enhanced silicon single-photon avalanche diode (SPAD) fabricated in a customized 0.13 $\mu$m CMOS technology is presented. The SPAD has a depleted absorption volume of approximately 15 $\mu$m x 15 $\mu$m x 18 $\mu$m.…
3D time-of-flight (ToF) imaging is used in a variety of applications such as augmented reality (AR), computer interfaces, robotics and autonomous systems. Single-photon avalanche diodes (SPADs) are one of the enabling technologies providing…
The demand for high-speed, low-latency, and energy-efficient object detection in autonomous systems -- such as advanced driver-assistance systems (ADAS), unmanned aerial vehicles (UAVs), and Industry 4.0 robotics -- has exposed the…
This study presents an efficient field-programmable gate array (FPGA) implementation of a polynomial spline function-based statistical compression algorithm designed to address the critical challenge of massive data transfer bandwidth in…
Spiking neural networks (SNNs) are powerful models of spatiotemporal computation and are well suited for deployment on resource-constrained edge devices and neuromorphic hardware due to their low power consumption. Leveraging attention…
Achieving fast and reliable temporal signal encoding is crucial for low-power, always-on systems. While current spike-based encoding algorithms rely on complex networks or precise timing references, simple and robust encoding models can be…
Spiking neural networks (SNNs), known for their low-power, event-driven computation and intrinsic temporal dynamics, are emerging as promising solutions for processing dynamic, asynchronous signals from event-based sensors. Despite their…
Massively parallel annealing processors may offer superior performance for a wide range of sampling and optimization problems. A key component dictating the size of these processors is the neuron update circuit, ideally implemented using…
Spiking neural networks (SNNs) are the third generation of neural networks and can explore both rate and temporal coding for energy-efficient event-driven computation. However, the decision accuracy of existing SNN designs is contingent…
Neuromorphic computing-modelled after the functionality and efficiency of biological neural systems-offers promising new directions for advancing artificial intelligence and computational models. Photonic techniques for neuromorphic…
A single-photon avalanche detector (SPAD) for high-speed quantum-key generation has successfully been developed. It has the highest photon detection repetition frequency and the lowest dark count rate in the world, as a board-mountable…