Recent advances of chemometric calibration methods in modern spectroscopy: Algorithms, strategy, and related issues
HP Wang, P Chen, JW Dai, D Liu, JY Li, YP Xu… - TrAC Trends in …, 2022 - Elsevier
In recent years, modern spectral analysis techniques, such as ultraviolet–visible (UV-vis)
spectroscopy, mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy, Raman …
spectroscopy, mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy, Raman …
[HTML][HTML] Machine learning techniques for analysis of hyperspectral images to determine quality of food products: A review
D Saha, A Manickavasagan - Current Research in Food Science, 2021 - Elsevier
Non-destructive testing techniques have gained importance in monitoring food quality over
the years. Hyperspectral imaging is one of the important non-destructive quality testing …
the years. Hyperspectral imaging is one of the important non-destructive quality testing …
A review of deep learning used in the hyperspectral image analysis for agriculture
C Wang, B Liu, L Liu, Y Zhu, J Hou, P Liu… - Artificial Intelligence …, 2021 - Springer
Hyperspectral imaging is a non-destructive, nonpolluting, and fast technology, which can
capture up to several hundred images of different wavelengths and offer relevant spectral …
capture up to several hundred images of different wavelengths and offer relevant spectral …
Application of deep learning in food: a review
L Zhou, C Zhang, F Liu, Z Qiu… - Comprehensive reviews in …, 2019 - Wiley Online Library
Deep learning has been proved to be an advanced technology for big data analysis with a
large number of successful cases in image processing, speech recognition, object detection …
large number of successful cases in image processing, speech recognition, object detection …
[HTML][HTML] Application of hyperspectral imaging systems and artificial intelligence for quality assessment of fruit, vegetables and mushrooms: A review
Highlights•Hyperspectral imaging is an effective tool for in assessing quality
parameters.•The most abundantly used wavelengths are 601–850 nm, used in over 50% of …
parameters.•The most abundantly used wavelengths are 601–850 nm, used in over 50% of …
[HTML][HTML] A tutorial on automatic hyperparameter tuning of deep spectral modelling for regression and classification tasks
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 …
chemometrics domain. A major topic in the deep learning (DL) modelling of spectral data is …
Hyperspectral imaging technology for quality and safety evaluation of horticultural products: A review and celebration of the past 20-year progress
In the past 20 years, hyperspectral imaging has been widely investigated as an emerging,
promising technology for evaluating quality and safety of horticultural products. This …
promising technology for evaluating quality and safety of horticultural products. This …
[HTML][HTML] Convolutional neural networks for image-based high-throughput plant phenotyping: a review
Plant phenotyping has been recognized as a bottleneck for improving the efficiency of
breeding programs, understanding plant-environment interactions, and managing …
breeding programs, understanding plant-environment interactions, and managing …
[HTML][HTML] Deep learning meets hyperspectral image analysis: A multidisciplinary review
Modern hyperspectral imaging systems produce huge datasets potentially conveying a great
abundance of information; such a resource, however, poses many challenges in the …
abundance of information; such a resource, however, poses many challenges in the …
Food and agro-product quality evaluation based on spectroscopy and deep learning: A review
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 …
internal and external quality evaluations of food and agro-products. Various linear and …