Hyperspectral technique combined with deep learning algorithm for detection of compound heavy metals in lettuce

•Vis-NIR HSI was used to detect compound heavy metals content in lettuce leaves.•WT-SCAE is proposed to obtain the deep spectral features.•Deep learning has a great potential for the identification of compound heavy metals content. The aim of this research was to develop a deep learning method which...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Food chemistry Jg. 321; S. 126503
Hauptverfasser:	Zhou, Xin, Sun, Jun, Tian, Yan, Lu, Bing, Hang, Yingying, Chen, Quansheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	England Elsevier Ltd 15.08.2020
Schlagworte:	cadmium Cadmium - analysis Compound heavy metals Deep learning heavy metals hyperspectral imagery Lactuca - chemistry Lactuca sativa lead Lead - analysis Least-Squares Analysis leaves Lettuce Nondestructive testing Plant Leaves - chemistry prediction Stack convolution auto encoder Support Vector Machine support vector machines wavelet Wavelet Analysis Wavelet transform Deep learning Lettuce Wavelet transform Compound heavy metals Nondestructive testing Stack convolution auto encoder
ISSN:	0308-8146, 1873-7072, 1873-7072
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!