Enhanced shuffle attention network based on visual working mechanism for high-resolution remote sensing image classification

Enhanced shuffle attention network based on visual working mechanism for high-resolution remote sensing image classification

AbstractHigh-resolution remote sensing images provide complete and detailed ground scenes. However, these complex and diverse details make it difficult to interpret large area objects and their small area details at a single granularity. Therefore, the method proposed in this paper refers to the pri...

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Bibliographic Details
Main Authors: Ming Cong, Jianjun Cui, Siliang Chen, Yihui Wang, Ling Han, Jiangbo Xi, Junkai Gu, Qingfang Zhang, Yiting Tao, Zhiye Wang, Miaozhong Xu, Hong Deng
Format: Article
Language:English
Published: Taylor & Francis Group 2024-02-01
Series:Geocarto International
Subjects:
Visual working memory
visual attention
visual reasoning
shuffle neural network
attention neural network
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2022.2143912

Internet

https://www.tandfonline.com/doi/10.1080/10106049.2022.2143912

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