相关论文: Cosmic Ray Rejection and Readout Efficiency for La…

The linear algorithm of the Wiener filter and constrained realizations (CRs) of Gaussian random fields is extended here to perform non-linear CRs. The procedure consists of: (1) Using low resolution data to constrain a high resolution…

The focus of this research is sensor applications including radar and sonar. Optimal sensing means achieving the best signal quality with the least time and energy cost, which allows processing more data. This paper presents novel work by…

We introduce a simple and efficient lossless image compression algorithm. We store a low resolution version of an image as raw pixels, followed by several iterations of lossless super-resolution. For lossless super-resolution, we predict…

Cardinality estimation algorithms receive a stream of elements whose order might be arbitrary, with possible repetitions, and return the number of distinct elements. Such algorithms usually seek to minimize the required storage and…

Ray tracing algorithm simulates the physical movements of a huge amount of rays to render a high quality image, in which the tracing procedure for each ray can be implemented in parallel. By leveraging the inherent parallelism of quantum…

Cosmic rays are the most outstanding example of accelerated particles. They are about 1\% of the total mass of the Universe, so that cosmic rays would represent by far the most important energy transformation process of the Universe.…

Over the next decade, improvements in cosmological parameter constraints will be driven by surveys of large-scale structure. Its inherent non-linearity suggests that significant information will be embedded in higher correlations beyond the…

In x-ray microscopy, traditional raster-scanning techniques are used to acquire a microscopic image in a series of step-scans. Alternatively, scanning the x-ray probe along a continuous path, called a fly-scan, reduces scan time and…

The growing urban complexity demands an efficient algorithm to acquire and process various sensor information from autonomous vehicles. In this paper, we introduce an algorithm to utilize object detection results from the image to…

Neutral atom quantum computers hold promise for scaling up to hundreds of thousands or more qubits, but their progress is constrained by slow qubit readout. Parallel measurement of qubit arrays currently takes milliseconds, much longer than…

The Telescope Array (TA) collaboration has measured the energy spectrum of ultra-high energy cosmic rays with primary energies above 1.6 x 10^(18) eV. This measurement is based upon four years of observation by the surface detector…

Single-particle cryo-electron microscopy (cryo-EM) is a leading technology to resolve the structure of molecules. Early in the process, the user detects potential particle images in the raw data. Typically, there are many false detections…

Data acquisition and analysis for the CODALEMA experiment, in operation for more than one year, has provided improved knowledge of the characteristics of this new device. At the same time, an important effort has been made to develop…

We discuss in detail the possibility of observing pairs of simultaneous parallel air showers produced by the fragments of cosmic ray nuclei which disintegrated in collisions with solar photons. We consider scenarios with different cosmic…

In this paper, we present a novel approach to the estimation of strongly varying backgrounds in astronomical images by means of small objects removal and subsequent missing pixels interpolation. The method is based on the analysis of a…

We present an objective method to remove the stellar continuum emission from narrow-band images to derive emission-line images. The method is based on the skewness of the pixel histogram of the residual images. Specifically, we exploit a…

Many algorithms have been proposed to help clinicians evaluate cone density and spacing, as these may be related to the onset of retinal diseases. However, there has been no rigorous comparison of the performance of these algorithms. In…

The standard approach to compressive sampling considers recovering an unknown deterministic signal with certain known structure, and designing the sub-sampling pattern and recovery algorithm based on the known structure. This approach…

Randomized smoothing is currently the state-of-the-art method that provides certified robustness for deep neural networks. However, due to its excessively conservative nature, this method of incomplete verification often cannot achieve an…

Many sensor networks, including large particle detector arrays measuring high-energy cosmic-ray air showers, traditionally rely on centralised trigger algorithms to find spatial and temporal coincidences of individual nodes. Such schemes…