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Application of Deep Learning in Spectral Analysis

Application of Deep Learning in Spectral Analysis

Hui Jiang / Quansheng Chen

114,17 €
IVA incluido
Disponible
Editorial:
KS OmniScriptum Publishing
Año de edición:
2024
Materia
Tecnología: cuestiones generales
ISBN:
9786208223816
114,17 €
IVA incluido
Disponible

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The deep learning approach combined with spectroscopic sensing techniques has shown great potential for quality evaluation of food and agro-products. Current advances in deep learning-based qualitative analysis include variety identification, geographical origin detection, adulteration recognition, and bruise detection, whereas quantitative analysis includes multiple component content prediction for fruits, grains, and crops. The main advantage of deep learning approach is the decreasing the dependence on human domain knowledge by end-to-end analysis and the improved precision and generalizability. This book discusses the current challenges of conventional chemometric methods and the emerging deep learning approach for spectral analysis. The research on exploring the learning mechanism of the ’black box’ deep learning model is discussed. This book focuses on the application of deep learning approaches on quality evaluation of food and agro-products, lessons from current studies, and future perspectives.

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