An efficient transformer architecture with depthwise separable convolutions for high-accuracy underwater acoustic target recognition

Abstract Underwater Acoustic Target Recognition (UATR) plays a vital role in maritime security and defense, requiring accurate and efficient classification of marine vessels based on their sonar acoustic emissions. Traditional recognition systems rely on handcrafted features and shallow classifiers,...

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Autores principales:	Nahid-Al Mahmud, Tao Zhang, Yasir Iqbal, Farhana Bari Sumona, Ikram Azaz, Yanzhang Geng, Wajid Khan, Qasem M. Kharma, Oleksandr Rubanenko
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Nature Portfolio 2025-12-01
Colección:	Scientific Reports
Materias:	Acoustic signal processing Depthwise separable convolution Feature extraction Transformer architecture Underwater acoustic signals Underwater target recognition
Acceso en línea:	https://doi.org/10.1038/s41598-025-32401-3
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