Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis.
Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved …

In recent years, modern spectral analysis techniques, such as ultraviolet–visible (UV-vis)
spectroscopy, mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy, Raman …

In recent years, extensive research in the field of Deep Learning (DL) has led to the
development of a wide array of machine learning algorithms dedicated to solving complex …

Fruit category identification is important in factories, supermarkets, and other fields. Current
computer vision systems used handcrafted features, and did not get good results. In this …

Learning patterns from spectra is critical for the development of chemometric analysis of
spectroscopic data. Conventional two-stage calibration approaches consist of data …

Recently, there has been an exponential growth in the number of publications focusing on
surface-enhanced Raman scattering (SERS), primarily driven by advancements in …

Background Rapid and non-destructive infrared spectroscopy has been applied to both
internal and external quality evaluations of food and agro-products. Various linear and …

Since the discovery of the inelastic scattering of light, ie, the so-called Raman effect, 1
Raman spectroscopy has become an attractive tool in a high number of research fields …

Food systems are negatively affected by food frauds with food recalls challenging the
system's sustainability and consumer confidence in food safety. Coffee, an economically …