About this Research Topic
Such techniques, being sustainable, noninvasive and nondestructive, could dramatically improve the quality of the final products, allowing the possibility to implement on-line, at-line and in-line quality control strategies.
In this collection, we explore recent optical and sensing-based procedures and techniques that may be applied to operate quality control and/or sorting over products and by-products in primary and secondary raw materials, agri-food, and pharmaceutical and chemical industries.
The topics of interest include spectrophotometry, image processing, machine learning and deep learning techniques, computer vision and chemical imaging applications able to improve existing quality control and/or sorting procedures or to develop novel ones.
We welcome manuscripts on original research, mini-reviews, short communication and perspectives.
Keywords: Image processing, Hyperspectral imaging, Spectrophotometry, Machine Learning, Deep learning, Chemometrics, Near Infrared Spectroscopy, primary and secondary raw material, quality control, sorting
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