LSACT: A Lightweight Compact Transformer With Spatial Attention for Complex Remote Sensing Scene Classification

Remote sensing scene classification remains a challenging task due to large variations in scale, viewpoint, texture, and the limited availability of annotated data. To address these challenges, this work presents the Lightweight Spatial Attention Compact Transformer (LSACT), a model that combines co...

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Autors principals:	Mohammed Q. Alkhatib, Ali Jamali
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Matèries:	Compact transformers convolutional neural networks (CNNs) deep learning scene classification vision transformers
Accés en línia:	https://ieeexplore.ieee.org/document/11554931/
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