Isbn: 9786208223816 - application of deep learning in spectral analysis (8 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. In English.

Taschenbuch. Condizione: Neu. Application of Deep Learning in Spectral Analysis | Hui Jiang (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786208223816 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 284 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Jiang HuiHui Jiang is a full professor in Jiangsu University and holds a PhD in Control Science and Engineering from the same university. His area of research includes the fabrication of olfactory and optical sensors for food analysi.…

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 284 pp. Englisch.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…