SGT: A Generalized Processing Model for 1-D Remote Sensing Signal Classification

This letter proposes a generalized feature extraction framework for 1-D remote sensing data. This approach streamlines the processing for extracting features by eliminating the need for some preprocessing, such as data normalization, data filtering, and spectrogram generation, which explicitly encod...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE geoscience and remote sensing letters 2022, Vol.19, p.1-5
Hauptverfasser:	Hu, Wei, Wang, Fangnian, Yin, Qiang, Zhang, Fan
Format:	Artikel
Sprache:	eng
Schlagworte:	Coders Data analysis Data processing Embedding Feature extraction Hyperspectral imaging Magnetic signals Modules Remote sensing Signal classification Signal processing Streamlines Transformers
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!