Transformer-Driven Semantic Relation Inference for Multilabel Classification of High-Resolution Remote Sensing Images

It is hard to use a single label to describe an image for the complexity of remote sensing scenes. Thus, it is a more general and practical choice to use multilabel image classification for high-resolution remote sensing (HRS) images. How to construct the relation between categories is a vital probl...

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Veröffentlicht in:	IEEE journal of selected topics in applied earth observations and remote sensing Jg. 15; S. 1884 - 1901
Hauptverfasser:	Tan, Xiaowei, Xiao, Zhifeng, Zhu, Jianjun, Wan, Qiao, Wang, Kai, Li, Deren
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Artificial neural networks Benchmarks Classification Correlation Deep convolutional neural network (DCNN) Feature extraction High resolution Image classification Image resolution Inference label dependence Long short-term memory Modules multilabel scene classification Neural networks Qualitative analysis Recurrent neural networks Remote sensing Resolution Roads semantic relation learning Semantic relations Semantics Task analysis Transformers
ISSN:	1939-1404, 2151-1535
Online-Zugang:	Volltext
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