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Optics Letters|June 1, 2016
Artificial neural network approaches for fluorescence lifetime imaging techniquesGang Wu, Thomas Nowotny, Yongliang Zhang, et al.Optics Express|July 14, 2016
Optimizing Laguerre expansion based deconvolution methods for analysing bi-exponential fluorescence lifetime imagesYongliang Zhang, Yu Chen, David Day-Uei LiOptics Letters|April 16, 2016
Fast bi-exponential fluorescence lifetime imaging analysis methods: publisher's noteDavid Day-Uei Li, Hongqi Yu, Yu ChenOptics Letters|February 14, 2015
Fast bi-exponential fluorescence lifetime imaging analysis methodsDavid Day-Uei Li, Hongqi Yu, Yu ChenOptics Express|November 19, 2016
Towards unsupervised fluorescence lifetime imaging using low dimensional variable projectionYongliang Zhang, Annie Cuyt, Wen-Shin Lee, et al.Optics Express|November 22, 2024
Object classification through heterogeneous fog with a fast data-driven algorithm using a low-cost single-photon avalanche diode arrayZhenya Zang, David Day Uei LiPhysics in Medicine and Biology|February 2, 2017
Comment on 'A novel method for fast and robust estimation of fluorescence decay dynamics using constrained least-square deconvolution with Laguerre expansion'Yongliang Zhang, David Day-Uei LiOptics Express|April 27, 2022
Spatial resolution improved fluorescence lifetime imaging via deep learningDong Xiao, Zhenya Zang, Wujun Xie, et al.Biomedical Optics Express|August 30, 2021
Histogram clustering for rapid time-domain fluorescence lifetime image analysisYahui Li, Natakorn Sapermsap, Jun Yu, et al.Methods and Applications in Fluorescence|March 2, 2023
Compact and robust deep learning architecture for fluorescence lifetime imaging and FPGA implementationZhenya Zang, Dong Xiao, Quan Wang, et al.Pageof 2,695