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Remote Sensing
  • Correction
  • Open Access

14 June 2022

Correction: Peng et al. A Fast Three-Dimensional Convolutional Neural Network-Based Spatiotemporal Fusion Method (STF3DCNN) Using a Spatial-Temporal-Spectral Dataset. Remote Sens. 2020, 12, 3888

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1
The State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.

Error in Affiliation

In the original article [1], there was an error regarding the affiliation 1. The word ‘Research’ was missing. The correct is as follows:
The State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China.

Error in Table

In the original article, there was a mistake in Table 5 as published in [1]. The ESTARFM and FSDAF results of CIA and LGC were rightly recorded yet wrongly calculated. The corrected Table 5 appears below.
Table 5. Running times 1 of the entire time series using different methods.
The authors apologize for any inconvenience caused and state that the scientific conclusions are unaffected. The original article has been updated.

Reference

  1. Peng, M.; Zhang, L.; Sun, X.; Cen, Y.; Zhao, X. A Fast Three-Dimensional Convolutional Neural Network-Based Spatiotemporal Fusion Method (STF3DCNN) Using a Spatial-Temporal-Spectral Dataset. Remote Sens. 2020, 12, 3888. [Google Scholar] [CrossRef]
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