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Han Li, Kean Chen, Lei Wang, Jianben Liu, Baoquan Wan and Bing Zhou
Thanks to the development of deep learning, various sound source separation networks have been proposed and made significant progress. However, the study on the underlying separation mechanisms is still in its infancy. In this study, deep networks are ex...
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Duncan M. FitzGerald, Zoe J. Hughes, Alice Staro, Christopher J. Hein, Md Mohiuddin Sakib, Ioannis Y. Georgiou and Alyssa Novak
When longshore transport systems encounter tidal inlets, complex mechanisms are involved in bypassing sand to downdrift barriers. Here, this process is examined at Plum Island Sound and Essex Inlets, Massachusetts, USA. One major finding from this study ...
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Marek Janusz Pluta, Daniel Tokarczyk and Jerzy Wiciak
Sound synthesis methods based on physical modelling of acoustic instruments depend on data that require measurements and recordings. If a musical instrument is operated by a human, a difficulty in filtering out variability is introduced due to a lack of ...
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Manuel Bou-Cabo, Guillermo Lara, Paula Gutiérrez-Muñoz, C. Saavedra, Ramón Miralles and Víctor Espinosa
Over the last decade, national authorities and European administrations have made great efforts to establish methodological standards for the assessment of underwater continuous noise, especially under the requirements set by the Marine Strategy Framewor...
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Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as...
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