Dimensionality reduction in surrogate modeling: A review of combined methods

CKJ Hou, K Behdinan - Data science and engineering, 2022 - Springer
Surrogate modeling has been popularized as an alternative to full-scale models in complex
engineering processes such as manufacturing and computer-assisted engineering. The …

Neural networks for hyperspectral imaging of historical paintings: a practical review

L Liu, T Miteva, G Delnevo, S Mirri, P Walter… - Sensors, 2023 - mdpi.com
Hyperspectral imaging (HSI) has become widely used in cultural heritage (CH). This very
efficient method for artwork analysis is connected with the generation of large amounts of …

[HTML][HTML] Dimensionality reduction and visualisation of hyperspectral ink data using t-SNE

BM Devassy, S George - Forensic science international, 2020 - Elsevier
Ink analysis is an important tool in forensic science and document analysis. Hyperspectral
imaging (HSI) captures large number of narrowband images across the electromagnetic …

Using t-distributed Stochastic Neighbor Embedding (t-SNE) for cluster analysis and spatial zone delineation of groundwater geochemistry data

H Liu, J Yang, M Ye, SC James, Z Tang, J Dong… - Journal of …, 2021 - Elsevier
Cluster analysis is a valuable tool for understanding spatial and temporal patterns (eg,
spatial zones) of groundwater geochemistry. To determine cluster numbers and cluster …

Application of Uniform Manifold Approximation and Projection (UMAP) in spectral imaging of artworks

M Vermeulen, K Smith, K Eremin, G Rayner… - … Acta Part A: Molecular …, 2021 - Elsevier
This study assesses the potential of Uniform Manifold Approximation and Projection (UMAP)
as an alternative tool to t-distributed Stochastic Neighbor Embedding (t-SNE) for the …

Predictive maintenance on the machining process and machine tool

A Jimenez-Cortadi, I Irigoien, F Boto, B Sierra… - Applied Sciences, 2019 - mdpi.com
This paper presents the process required to implement a data driven Predictive
Maintenance (PdM) not only in the machine decision making, but also in data acquisition …

Unsupervised clustering of hyperspectral paper data using t-SNE

B Melit Devassy, S George, P Nussbaum - Journal of imaging, 2020 - mdpi.com
For a suspected forgery that involves the falsification of a document or its contents, the
investigator will primarily analyze the document's paper and ink in order to establish the …

[HTML][HTML] t-SNE: A study on reducing the dimensionality of hyperspectral data for the regression problem of estimating oenological parameters

R Silva, P Melo-Pinto - Artificial Intelligence in Agriculture, 2023 - Elsevier
In recent years there is a growing importance in using machine learning techniques to
improve procedures in precision agriculture: in this work we perform a study on models …

1D convolutional neural network for the discrimination of aristolochic acids and their analogues based on near-infrared spectroscopy

X Chen, Q Chai, N Lin, X Li, W Wang - Analytical Methods, 2019 - pubs.rsc.org
Chinese herbs containing aristolochic acids (AAs) have been implicated in renal failure and
urothelial carcinoma. The detection of AAs and their analogues is significant for the correct …

XRFast a new software package for processing of MA-XRF datasets using machine learning

M Vermeulen, A McGeachy, B Xu, H Chopp… - Journal of Analytical …, 2022 - pubs.rsc.org
X-ray fluorescence (XRF) spectroscopy is a common technique in the field of heritage
science. However, data processing and data interpretation remain a challenge as they are …