相关论文: Hyperspectral Neutron CT with Material Decompositi…

Physics-informed neural networks (NN) are an emerging technique to improve spatial resolution and enforce physical consistency of data from physics models or satellite observations. A super-resolution (SR) technique is explored to…

Microscopy has been key to tremendous advances in science, technology, and medicine, revealing structure and dynamics across time and length scales. However, combining high spatial and temporal resolution in a non-invasive, label-free…

Nuclear electric resonance (NER) spectroscopy is currently experiencing a revival as a tool for nuclear spin-based quantum computing. Compared to magnetic or electric fields, local electron density fluctuations caused by changes in the…

Resonant dielectric nanoparticles (RDNs) made of materials with large positive dielectric permittivity, such as Si, GaP, GaAs, have become a powerful platform for modern light science, enabling various fascinating applications in…

Radiation exposure in positron emission tomography (PET) imaging limits its usage in the studies of radiation-sensitive populations, e.g., pregnant women, children, and adults that require longitudinal imaging. Reducing the PET radiotracer…

1D or 2D neutron imaging detectors with individual wire or strip readout using discriminators have the advantage of being able to treat several neutron impacts partially overlapping in time, hence reducing global dead time. A single neutron…

Cryo-electron microscopy (cryo-EM) has achieved near-atomic level resolution of biomolecules by reconstructing 2D micrographs. However, the resolution and accuracy of the reconstructed particles are significantly reduced due to the…

In low light or short-exposure photography the image is often corrupted by noise. While longer exposure helps reduce the noise, it can produce blurry results due to the object and camera motion. The reconstruction of a noise-less image is…

In this paper, we extend our previous work on the Expressive Neural Network (ENN), a multilayer perceptron with adaptive activation functions parametrized using the Discrete Cosine Transform (DCT). Building upon previous work that…

Functional nanomaterials, including 2D materials and their heterostructures are expected to impact fields ranging from catalysis, optoelectronics to nanophotonics. To realize their potential, novel experimental approaches need to be…

Associated particle imaging (API) is a non-destructive nuclear technique for the 3D determination of isotopic distributions. By detecting the alpha particle associated with the emitted neutron in the deuterium-tritium fusion reaction with a…

Cyclotron Radiation Emission Spectroscopy (CRES) is an approach to measuring the energy of an electron trapped in an externally applied magnetic field. The bare electron can come from different interactions, including photoelectric…

Low-dose emission tomography (ET) plays a crucial role in medical imaging, enabling the acquisition of functional information for various biological processes while minimizing the patient dose. However, the inherent randomness in the photon…

Energy-based models parameterize the unnormalized log-probability of data samples, but there is a lack of guidance on how to construct the "energy". In this paper, we propose a Denoising-EBM which decomposes the image energy into "semantic…

Transmission electron microscope (TEM) images are often corrupted by noise, hindering their interpretation. To address this issue, we propose a deep learning-based approach using simulated images. Using density functional theory…

Hadamard Transform Spectral Imaging (HTSI) is a multiplexing technique used to recover spectra via encoding with multi-slit masks, and is particularly useful in low photon flux applications where signal-independent noise is the dominant…

Recently, a new neutron spectroscopy for the dynamics in complex (bio-) systems has been proposed [A. Benedetto, and G. J. Kearley, Sci. Rep. 6, 34266, (2016)]. This spectroscopy is ideal where only the overall relaxation time in a…

Neutron imaging is a non-destructive technique for analyzing a wide class of samples, such as archaeological or industrial material structures. In recent decades, technological advances have had a great impact on the neutron imaging…

In this article, we address the challenges of image super-resolution and noise reduction, which are crucial for enhancing the quality of images derived from low-resolution or noisy data. We compared and assessed several approaches for…

Dual energy X-ray Computed Tomography (DECT) enables to automatically decompose materials in clinical images without the manual segmentation using the dependency of the X-ray linear attenuation with energy. In this work we propose a deep…