Related papers: Improved methodologies to study the performance of…
We study the efficiency of a neural-net filter and deconvolution method for estimating jet energies and spectra in high-background reactions such as nuclear collisions at the relativistic heavy-ion collider and the large hadron collider.…
The possibility to resolve narrow structures in reaction cross sections in calculations with the Lorentz integral transform (LIT) method is studied. To this end we consider a fictitious two-nucleon problem with a low-lying and narrow…
In order to deal with the sparse and unstructured raw point clouds, LiDAR based 3D object detection research mostly focuses on designing dedicated local point aggregators for fine-grained geometrical modeling. In this paper, we revisit the…
There has been an increasing interest in the monitoring of nuclear fuel for power reactors by detecting the anti-neutrinos produced during operation. Small liquid scintillator detectors have already demonstrated sensitivity to operational…
The next generation of ground-based gravitational-wave detectors, Einstein Telescope (ET) and Cosmic Explorer (CE), present a unique opportunity to put constraints on dense matter, among many other groundbreaking scientific goals. In a…
Recently, a growing interest has been seen in deep learning-based semantic segmentation. UNet, which is one of deep learning networks with an encoder-decoder architecture, is widely used in medical image segmentation. Combining multi-scale…
Renal cancer is one of the most prevalent cancers worldwide. Clinical signs of kidney cancer include hematuria and low back discomfort, which are quite distressing to the patient. Some surgery-based renal cancer treatments like laparoscopic…
A method for absolute calibration of a photon-number resolving detector producing analog signals as the output is developed using a twin beam. The method gives both analog-to-digital conversion parameters and quantum detection efficiency…
Results of experimental investigations of a neutron resonances width in planar waveguides using the time-of-flight reflectometer REMUR of the IBR-2 pulsed reactor are reported and comparison with theoretical calculations is presented. The…
Detection of malignant lesions on mammography images is extremely important for early breast cancer diagnosis. In clinical practice, images are acquired from two different angles, and radiologists can fully utilize information from both…
Medical image segmentation, a crucial task in computer vision, facilitates the automated delineation of anatomical structures and pathologies, supporting clinicians in diagnosis, treatment planning, and disease monitoring. Notably,…
A novel image processing technique based on convolution is developed for analyzing the etch-pit images in Nuclear Track Detectors (NTDs). The outcomes of the application of the proposed method on the different types of NTDs (e.g., CR-39,…
As PET imaging is accompanied by substantial radiation exposure and cancer risk, reducing radiation dose in PET scans is an important topic. However, low-count PET scans often suffer from high image noise, which can negatively impact image…
We discuss the proposal of Freedman, Ringo, and Dombeck to search for the neutron electric dipole moment use of the acceleration of neutrons in an inhomogeneous electric field followed by amplification of the resulting displacement by…
The importance of some atom hydrogen collisions in AGN has been investigated. The results are useful for better estimate of the hydrogen Balmer lines uxes, which usage for effective temperature diagnostics in astrophysical plasma is limited…
Extensive work has demonstrated the effectiveness of Vision Transformers. The plain Vision Transformer tends to obtain multi-scale features by selecting fixed layers, or the last layer of features aiming to achieve higher performance in…
Kidney tumor segmentation emerges as a new frontier of computer vision in medical imaging. This is partly due to its challenging manual annotation and great medical impact. Within the scope of the Kidney Tumor Segmentation Challenge 2019,…
The ENUBET ERC project (2016-2021) is studying a narrow band neutrino beam where lepton production can be monitored at single particle level in an instrumented decay tunnel. This would allow to measure $\nu_{\mu}$ and $\nu_{e}$ cross…
Pulsed beams have tremendous advantages for precision experiments with cold neutrons. In order to minimise and measure systematic effects, they are used at continuous sources in spite of the related substantial decrease in intensity. At the…
Recently, transformer networks have outperformed traditional deep neural networks in natural language processing and show a large potential in many computer vision tasks compared to convolutional backbones. In the original transformer,…