Remote Sensing Change Detection Based on Unsupervised Multi-Attention Slow Feature Analysis

Remote Sensing Change Detection Based on Unsupervised Multi-Attention Slow Feature Analysis

With the development of big data, analyzing the environmental benefits of transportation systems by artificial intelligence has become a hot issue in recent years. The ground traffic changes can be overlooked from a high-altitude perspective, using the technology of multi-temporal remote sensing cha...

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Bibliographic Details
Main Authors: Weipeng Jing, Songyu Zhu, Peilun Kang, Jian Wang, Shengjia Cui, Guangsheng Chen, Houbing Song
Format: Article
Language:English
Published: MDPI AG 2022-06-01
Series:Remote Sensing
Subjects:
remote sensing
unsupervised change detection
deep learning
slow feature analysis
multi-attention
Online Access:https://www.mdpi.com/2072-4292/14/12/2834

Internet

https://www.mdpi.com/2072-4292/14/12/2834

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