期刊论文

Tao Lei<&wdkj&>Tao Lei Tao Lei Tao Lei

英文

智能技术学报

2468-2322

2023

8

4

1178-1190

10.1049/cit2.12208

This work was supported in part by the National Natural Science Foundation of China under Grant 62201452, 2271296 and 62201453, in part by the Natural Science Basic Research Programme of Shaanxi under Grant 2022JQ‐592, in part by the Special Construction Fund for Key Disciplines of Shaanxi Provincial Higher Education, in part by the Natural Science Basic Research Program of Shaanxi under Grant 2021JC‐47, and in part by Scientific Research Program Funded by Shaanxi Provincial Education Department under Grant 22JK0568.

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Aerial scene recognition (ASR) has attracted great attention due to its increasingly essential applications. Most of the ASR methods adopt the multi-scale architecture because both global and local features play great roles in ASR. However, the existing multi-scale methods neglect the effective interactions among different scales and various spatial locations when fusing global and local features, leading to a limited ability to deal with challenges of large-scale variation and complex background in aerial scene images. In addition, existing methods may suffer from poor generalisations due to ...