Compressing deep-quaternion neural networks with targeted regularisation

Compressing deep-quaternion neural networks with targeted regularisation

In recent years, hyper-complex deep networks (such as complex-valued and quaternion-valued neural networks – QVNNs) have received a renewed interest in the literature. They find applications in multiple fields, ranging from image reconstruction to 3D audio processing. Similar to their real-valued co...

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Bibliographic Details
Main Authors: Riccardo Vecchi, Simone Scardapane, Danilo Comminiello, Aurelio Uncini
Format: Article
Language:English
Published: Wiley 2020-07-01
Series:CAAI Transactions on Intelligence Technology
Subjects:
neural nets
image reconstruction
learning (artificial intelligence)
image coding
compact networks
sparsified qvnn
regularised qvnn
structured regularisations
complex-valued quaternion-valued neural networks
regularisation approaches
real-world applications
3d audio processing
hyper-complex deep networks
Online Access:https://digital-library.theiet.org/content/journals/10.1049/trit.2020.0020

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https://digital-library.theiet.org/content/journals/10.1049/trit.2020.0020

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