[HTML][HTML] Near-infrared spectroscopy and machine learning for classification of food powders during a continuous process
In food production environments, the wrong powder material is occasionally loaded onto a
production line which impacts food safety, product quality, and production economics. The …
production line which impacts food safety, product quality, and production economics. The …
Deep Learning in Estimation of Fruit Attributes Using Near Infrared Spectroscopy
J Walsh - 2024 - acquire.cqu.edu.au
Determining the Dry Matter Content (DMC) of mango fruit is important for assessing harvest
maturity and ensuring the quality of the ripened fruit. Near Infrared (NIR) spectroscopy offers …
maturity and ensuring the quality of the ripened fruit. Near Infrared (NIR) spectroscopy offers …
Process of analyzing organic materials, based on processing of near infrared spectra through advanced methods
D Tegegn - 2023 - boa.unimib.it
Near-infrared spectroscopy is a mature technique continuing to demonstrate steady
progress. This is thanks to cutting-edge developments of new handheld spectrometers …
progress. This is thanks to cutting-edge developments of new handheld spectrometers …
Explore the effect of data augmentation of spectroscopic data for deep learning models
T Naveed - 2022 - nmbu.brage.unit.no
This study aimed to explore the effect of data augmentation techniques to improve the
performance of deep learning models on data sets that contain more features than samples …
performance of deep learning models on data sets that contain more features than samples …
[PDF][PDF] Rapid Analysis of Powders Based on Deep Learning, Near-Infrared and Derivative Spectroscopy.
Infrared spectroscopy has proved to be a powerful tool for solving organic chemistry
problems and finds a widening field in many industries. Infrared absorption and its relation to …
problems and finds a widening field in many industries. Infrared absorption and its relation to …