相关论文: Experimental Studies on Spatial Resolution of a De…
We present our current progress on the design and test of Ti/TiN Multilayer for use in Kinetic Inductance Detectors (KIDs). Sensors based on sub-stoichiometric TiN film are commonly used in several applications. However, it is difficult to…
We apply machine learning methods to demonstrate range superresolution in remote sensing radar detection. Specifically, we implement a denoising autoencoder to estimate the distance between two equal intensity scatterers in the…
Traditional radar imaging methods suffer from the problems of low resolution and poor noise suppression. We propose a new radar imaging method based on Self-supervised deep-learning-assisted compressed sensing (SS-DL-CS-Net). The original…
We demonstrate a prototype kinetic inductance detector (KID) readout system that uses less than 10 mW per pixel. The CCAT-prime RFSoC based readout is capable of reading four independent detector networks of up to 1000 KIDs each. The power…
The development of wide-area cryogenic light detectors with baseline energy resolution lower than 20 eV RMS is essential for next generation bolometric experiments searching for rare interactions. Indeed the simultaneous readout of the…
Recent years have witnessed the unprecedented success of deep convolutional neural networks (CNNs) in single image super-resolution (SISR). However, existing CNN-based SISR methods mostly assume that a low-resolution (LR) image is bicubicly…
Computed Tomography (CT) imaging technique is widely used in geological exploration, medical diagnosis and other fields. In practice, however, the resolution of CT image is usually limited by scanning devices and great expense. Super…
An experimental setup is proposed for the precise measurement of the quantum states of ultracold neutrons bound in the earth's gravitational field. The experiment utilizes a CCD-based pixel sensor and magnification system to observe the…
Compressed sensing (CS) is a powerful method routinely employed to accelerate image acquisition. It is particularly suited to situations when the image under consideration is sparse but can be sampled in a basis where it is non-sparse. Here…
As a space telescope, the China Space Station Survey Telescope (CSST) will face significant challenges from cosmic ray (CR) contamination. These CRs will severely degrade image quality and further influence scientific analysis. Due to the…
Quantum key distribution (QKD) provides information-theoretic security and satellite-based quantum key distribution (SatQKD) has demonstrated the potential to extend this communication security to intercontinental scales. However,…
Cosmic-Ray Neutron Sensing (CRNS) is a novel technique for determining environmental water content by measuring albedo neutrons in the epithermal to fast energy range with moderated neutron detectors. We have investigated the response…
As robotics and augmented reality applications increasingly rely on precise and efficient 6D object pose estimation, real-time performance on edge devices is required for more interactive and responsive systems. Our proposed Sparse…
We have solved numerically the diffusive Usadel equations that describe the spatially-varying superconducting proximity effect in Ti-Al thin-film bi- and trilayers with thickness values that are suitable for Kinetic Inductance Detectors…
Image steganalysis is a special binary classification problem that aims to classify natural cover images and suspected stego images which are the results of embedding very weak secret message signals into covers. How to effectively suppress…
Resistive AC-coupled Silicon Detectors (RSDs) are based on the Low Gain Avalanche Diode (LGAD) technology, characterized by a continuous gain layer, and by the innovative introduction of resistive read-out. Thanks to a novel electrode…
Superconducting NbN wires have recently received attention as detectors for visible and infrared photons. We present experiments in which we use a NbN wire for high-efficiency (40 %) detection of single electrons with keV energy. We use the…
Prior methodologies have disregarded the diversities among distinct degradation types during image reconstruction, employing a uniform network model to handle multiple deteriorations. Nevertheless, we discover that prevalent degradation…
The solution of nonlinear electromagnetic (EM) inverse scattering problems is typically hindered by several challenges such as ill-posedness, strong nonlinearity, and high computational costs. Recently, deep learning has been demonstrated…
For a long time, scintillator detectors have suffered from relatively weak spatial resolution due to various influencing factors. Additionally, the high cost of photomultiplier tubes (PMTs) has limited the widespread adoption of…