Deep Convolutional Neural Network for Detection and Prediction of Waxy Corn Seed Viability Using Hyperspectral Reflectance Imaging

This paper aimed to combine hyperspectral imaging (378–1042 nm) and a deep convolutional neural network (DCNN) to rapidly and non-destructively detect and predict the viability of waxy corn seeds. Different viability levels were set by artificial aging (aging: 0 d, 3 d, 6 d, and 9 d), and spectral d...

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Egile Nagusiak:	Xiaoqing Zhao, Lei Pang, Lianming Wang, Sen Men, Lei Yan
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	MDPI AG 2022-12-01
Saila:	Mathematical and Computational Applications
Gaiak:	hyperspectral imaging deep convolutional neural network waxy corn seeds viability detection
Sarrera elektronikoa:	https://www.mdpi.com/2297-8747/27/6/109
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