3 citations · 4 across the 9 of their papers we have counts for
12 papers
On-Device Super-Resolution Imaging for a Low-Cost SPAD Array on a 640-KB-SRAM Microcontroller
Zhenya Zang, Istvan Gyongy, Mike Davies
This work presents a super-resolution (SR) deep-learning (DL) architecture to simultaneously upscale low-resolution (LR) depth and intensity images acquired by a consumer-grade VL5…
Histogramless Time-Domain Sketched Fluorescence Lifetime Imaging
Zhenya Zang, Istvan Gyongy, Mike Davies
We present a statistics-aware compression strategy that processes photon timestamps directly from time-correlated single-photon counting (TCSPC) modules for time-domain fluorescenc…
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…
FPGA Implementation of Sketched LiDAR for a 192 x 128 SPAD Image Sensor
Zhenya Zang, Mike Davies, Istvan Gyongy
This study presents an efficient field-programmable gate array (FPGA) implementation of a polynomial spline function-based statistical compression algorithm designed to address the…
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…
Cerebral blood flow monitoring using a deep learning implementation of the two-layer DCS analytical model with a 512x512 SPAD array
Mingliang Pan, Chenxu Li, Yuanzhe Zhang +8
Diffuse correlation spectroscopy (DCS) analyzes the autocorrelation function of photons scattered by red blood cells, enabling non-invasive, continuous measurement of deep tissue b…
Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining
Zhenya Zang, David A Dorward, Katherine E Quiohilag +4
The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essential step in guiding treatment options and prognosis. However, current clinical p…
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,…
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…
Compact and Robust Deep Learning Architecture for Fluorescence Lifetime Imaging and FPGA Implementation
Zhenya Zang, Dong Xiao, Quan Wang +3
This paper reported a bespoke adder-based deep learning network for time-domain fluorescence lifetime imaging (FLIM). By leveraging the l1-norm extraction method, we propose a 1-D…
Fast fluorescence lifetime imaging analysis via extreme learning machine
Zhenya Zang, Dong Xiao, Quan Wang +4
We present a fast and accurate analytical method for fluorescence lifetime imaging microscopy (FLIM) using the extreme learning machine (ELM). We used extensive metrics to evaluate…