Scan-specific artifact reduction in k-space (SPARK) neural networks synergize with physics-based reconstruction to accelerate MRI
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Localised and high-frequency measurements of the global horizontal irradiance (GHI) are a key information to assess the level of power production of distributed photovoltaic generation. The paper presents a supervised machine learning-based procedure to es ...
Online learning with streaming data in a distributed and collaborative manner can be useful in a wide range of applications. This topic has been receiving considerable attention in recent years with emphasis on both single-task and multitask scenarios. In ...
The multitask diffusion LMS is an efficient strategy to simultaneously infer, in a collaborative manner, multiple parameter vectors. Existing works on multitask problems assume that all agents respond to data synchronously. In several applications, agents ...
In spatially encoded MRI, the signal is acquired sequentially for different coordinates. In particular for single-scan acquisitions in inhomogeneous fields, spatially encoded methods improve the image quality compared to traditional k-space encoding. Previ ...
Amplitude demodulation (AM) is a signal decomposition technique by which a signal can be decomposed to a product of two signals, i.e, a quickly varying carrier and a slowly varying modulator. In this work, the probabilistic amplitude demodulation (PAD) fea ...
The local tie vector, which connects the different space geodetic techniques at a co-located site, plays an important role in the realization of the International Terrestrial Reference Frame (ITRF). This paper presents a new method to determine the tie vec ...
Abstract Amplitude demodulation (AM) is a signal decomposition technique by which a signal can be decomposed to a product of two signals, i.e, a quickly varying carrier and a slowly varying modulator. In this work, the probabilistic amplitude demodulation ...
Amplitude demodulation (AM) is a signal decomposition technique by which a signal can be decomposed to a product of two signals, i.e, a quickly varying carrier and a slowly varying modulator. In this work, the probabilistic amplitude demodulation (PAD) fea ...
This paper presents a remote sensing technique for calibrating hydrodynamics models, which is particularly useful when access to the riverbed for a direct measure of flow variables may be precluded. The proposed technique uses terrestrial photography and a ...
Adaptive networks are suitable for decentralized inference tasks. Recent works have intensively studied distributed optimization problems in the case where the nodes have to estimate a single optimum parameter vector collaboratively. However, there are man ...
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