Cargando…
Hyperspectral Image-Based Variety Classification of Waxy Maize Seeds by the t-SNE Model and Procrustes Analysis
Variety classification is an important step in seed quality testing. This study introduces t-distributed stochastic neighbourhood embedding (t-SNE), a manifold learning algorithm, into the field of hyperspectral imaging (HSI) and proposes a method for classifying seed varieties. Images of 800 maize...
Autores principales: | Miao, Aimin, Zhuang, Jiajun, Tang, Yu, He, Yong, Chu, Xuan, Luo, Shaoming |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308723/ https://www.ncbi.nlm.nih.gov/pubmed/30545028 http://dx.doi.org/10.3390/s18124391 |
Ejemplares similares
-
Spectral and Image Integrated Analysis of Hyperspectral Data for Waxy Corn Seed Variety Classification
por: Yang, Xiaoling, et al.
Publicado: (2015) -
Application of hyperspectral imaging and chemometrics for variety classification of maize seeds
por: Zhao, Yiying, et al.
Publicado: (2018) -
Unsupervised Clustering of Hyperspectral Paper Data Using t-SNE
por: Melit Devassy, Binu, et al.
Publicado: (2020) -
Application of near-infrared hyperspectral imaging to identify a variety of silage maize seeds and common maize seeds
por: Bai, Xiulin, et al.
Publicado: (2020) -
Application of Hyperspectral Imaging and Chemometric Calibrations for Variety Discrimination of Maize Seeds
por: Zhang, Xiaolei, et al.
Publicado: (2012)