Optimizing and Evaluating Swin Transformer for Aircraft Classification: Analysis and Generalizability of the MTARSI Dataset

Optimizing and Evaluating Swin Transformer for Aircraft Classification: Analysis and Generalizability of the MTARSI Dataset

Aircraft classification via remote sensing images has many commercial and military applications. The Swin-Transformer has shown great promise, recently dominating general-purpose image classification benchmarks such as ImageNet. In this paper, we test whether the performance of the Swin-Transformer...

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Bibliographic Details
Main Authors: Kyle Gao, Hongjie He, Dening Lu, Linlin Xu, Lingfei Ma, Jonathan Li
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Aircraft classification
deep learning
MTARSI dataset
out-of-distribution
remote sensing
self-attention
Online Access:https://ieeexplore.ieee.org/document/9996354/

Internet

https://ieeexplore.ieee.org/document/9996354/

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