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- Title
Retrieval of Chemical Oxygen Demand through Modified Capsule Network Based on Hyperspectral Data.
- Authors
Deng, Chubo; Zhang, Lifu; Cen, Yi
- Abstract
This study focuses on the retrieval of chemical oxygen demand (COD) in the Baiyangdian area in North China, using a modified capsule network. Herein, the capsule model was modified to analyze the regression relationship between 1-D hyperspectral data and COD values. The results indicate there is a statistically significant correlation between COD and the hyperspectral data. The accuracy of the capsule network was compared with the results obtained from using a traditional back-propagation neural network (BP) method. The capsule network achieved superior accuracy with fewer iterations, compared with the BP algorithm. An R2 value of 0.78 was obtained against measured COD values retrieved using the capsule network method, compared with a value of 0.42 for the BP algorithm retrievals. This suggests the capsule network method has great potential to solve regression problems in the field of remote sensing.
- Subjects
CHINA; CHEMICAL oxygen demand; DATABASES; REMOTE sensing
- Publication
Applied Sciences (2076-3417), 2019, Vol 9, Issue 21, p4620
- ISSN
2076-3417
- Publication type
Article
- DOI
10.3390/app9214620