Deep spectral modelling for regression and classification is gaining popularity in the
chemometrics domain. A major topic in the deep learning (DL) modelling of spectral data is …

Data scarcity is a major challenge when training deep learning (DL) models. DL demands a
large amount of data to achieve exceptional performance. Unfortunately, many applications …

Deep learning (DL) is emerging as a new tool to model spectral data acquired in analytical
experiments. Although applications are flourishing, there is also much interest currently …

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 …

Handwriting recognition is a multi-step process that includes data collection, preprocessing,
feature extraction, and classification in order to create a final prediction. This process …

People with autistic spectrum disorders (ASDs) have difficulty recognizing and engaging
with others. The symptoms of ASD may occur in a wide range of situations. There are …

Calibration transfer (CT) refers to the set of chemometric techniques used to transfer (near-
infrared) calibration models between spectrometers. The requirement of traditional CT …

In spectral data predictive modelling of fresh fruit, often the models are calibrated to predict
multiple responses. A common method to deal with such a multi-response predictive …

Autism spectrum disorder (ASD) is a neurological illness characterized by deficits in
cognition, physical activities, and social skills. There is no specific medication to treat this …

Calibration transfer (CT) is required when a model developed on one instrument needs to
be transferred and used on a new instrument. Several methods are available in the …