6 papers
On-Device Super Resolution Imaging Using Low-Cost SPAD Array and Embedded Lightweight Deep Learning
Zhenya Zang, Xingda Li, David Day Uei Li
This work presents a lightweight super-resolution (LiteSR) neural network for depth and intensity images acquired from a consumer-grade single-photon avalanche diode (SPAD) array w…
Online Learning Extreme Learning Machine with Low-Complexity Predictive Plasticity Rule and FPGA Implementation
Zhenya Zang, Xingda Li, David Day Uei Li
We propose a simplified, biologically inspired predictive local learning rule that eliminates the need for global backpropagation in conventional neural networks and membrane integ…
Towards On-Device Learning and Reconfigurable Hardware Implementation for Encoded Single-Photon Signal Processing
Zhenya Zang, Xingda Li, David Day Uei Li
Deep neural networks (DNNs) enhance the accuracy and efficiency of reconstructing key parameters from time-resolved photon arrival signals recorded by single-photon detectors. Howe…
Spiking Neural Network Enhanced Hand Gesture Recognition Using Low-Cost Single-photon Avalanche Diode Array
Zhenya Zang, Xingda Li, David Day Uei Li
We present a compact spiking convolutional neural network (SCNN) and spiking multilayer perceptron (SMLP) to recognize ten different gestures in dark and bright light environments,…
Enhancing Blood Flow Assessment in Diffuse Correlation Spectroscopy: A Transfer Learning Approach with Noise Robustness Analysis
Xi Chen, Xingda Li
Diffuse correlation spectroscopy (DCS) is an emerging noninvasive technique that measures the tissue blood flow, by using near-infrared coherent point-source illumination to detect…
Fast Cerebral Blood Flow Analysis via Extreme Learning Machine
Xi Chen, Zhenya Zang, Xingda Li
We introduce a rapid and precise analytical approach for analyzing cerebral blood flow (CBF) using Diffuse Correlation Spectroscopy (DCS) with the application of the Extreme Learni…