Enhancing feature learning of hyperspectral imaging using shallow autoencoder by adding parallel paths encoding

Abstract Conventional image formats have limited information conveyance, while Hyperspectral Imaging (HSI) offers a broader representation through continuous spectral bands, capturing hundreds of spectral features. However, this abundance leads to redundant information, posing a computational challe...

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Bibliografische Detailangaben

Hauptverfasser:	Bibi Noor Asmat, Hafiz Syed Muhammad Bilal, M. Irfan Uddin, Faten Khalid Karim, Samih M. Mostafa, José Varela-Aldás
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Nature Portfolio 2025-05-01
Schriftenreihe:	Scientific Reports
Schlagworte:	Classification Autoencoder CNN Feature learning Hyperspectral imaging Remote sensing
Online-Zugang:	https://doi.org/10.1038/s41598-025-01758-w
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