activity
20202026
most citedA Review of 1D Convolutional Neural Networks toward Unknown Substance Identification in Portable Raman Spectrometer

35 citations · 47 across the 4 of their papers we have counts for

collaborators

5 papers

cond-mat.mes-hall2026

Establishing the role of thickness in LaOBr; an alternative gate dielectric for vdW heterostructures

Isaac Antoine Lagaud, Justin Boddison-Chouinard, Antoine Labbé +9

In electronic devices, the quality of the dielectric material is determined by figures of merit such as the band gap, leakage onset field, breakdown field and the number of built-i…

q-bio.QM2021

Spectral unmixing of Raman microscopic images of single human cells using Independent Component Analysis

M. Hamed Mozaffari, Li-Lin Tay

Application of independent component analysis (ICA) as an unmixing and image clustering technique for high spatial resolution Raman maps is reported. A hyperspectral map of a fixed…

cs.CV2021★ 9 cited

Raman spectral analysis of mixtures with one-dimensional convolutional neural network

M. Hamed Mozaffari, Li-Lin Tay

Recently, the combination of robust one-dimensional convolutional neural networks (1-D CNNs) and Raman spectroscopy has shown great promise in rapid identification of unknown subst…

eess.SP2021★ 3 cited

One-dimensional Active Contour Models for Raman Spectrum Baseline Correction

M. Hamed Mozaffari, Li-Lin Tay

Raman spectroscopy is a powerful and non-invasive method for analysis of chemicals and detection of unknown substances. However, Raman signal is so weak that background noise can d…

eess.SP2020★ 35 cited

A Review of 1D Convolutional Neural Networks toward Unknown Substance Identification in Portable Raman Spectrometer

M. Hamed Mozaffari, Li-Lin Tay

Raman spectroscopy is a powerful analytical tool with applications ranging from quality control to cutting edge biomedical research. One particular area which has seen tremendous a…