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Showing 1 to 6 of 6 for “"Implicit Neural Representations"”.
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Hyperspectral image compression using implicit neural representations
… data. In this thesis, we develop several neural compression-based methods for hyperspectral images. Our methodology relies on transforming hyperspectral images into implicit neural representations (INR), specifically neural functions that establish a correspondence between coordinates and …
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Implicit neural representations for time-frequency signal processing
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms
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Implicit Neural Representations for Multimedia Compression [Rappresentazioni neurali implicit per la Compressione di Multimedia]
Nelle rappresentazioni neurali implicite (INR) un segnale discreto viene interpretato come una funzione continua dalle coordinate ai campioni e una rete neurale viene poi allenata per approssimare questa funzione. I parametri della rete risultante possono essere compressi per ridurre la …
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Data Compression with Relative Entropy Coding
… using small, energy-efficient, probabilistic neural networks called Bayesian implicit neural representations. Finally, while most of the work I present in the thesis was motivated by practical data compression, many of the techniques I present are more general and have implications and …
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Neural implicit representations for engineering design
… of parameters that are also limited in number. Implicit neural representations are gaining popularity in 3D geometry representations, because of their capabilities to represent diverse set of designs in a fixed length latent vector space. So, the goal of this thesis is to demonstrate the best …
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From Discrete to Continuous: Learning 3D Geometry from Unstructured Points by Random Continuous Space Queries
… to achieve more robust, invariant, and versatile implicit neural representations (INR) of 3D shapes. In recent efforts to explore point-cloud based learning methods to improve 3D shape analysis, there has been much attention paid to the use of INR-based frameworks. Existing methods, however, …