相关论文: Classifying Complex Faraday Spectra with Convoluti…

The Polarisation Sky Survey of the Universe's Magnetism (POSSUM) will conduct a sensitive $\sim$1 GHz radio polarization survey covering 20 000 square degrees of the Southern sky with the Australian Square Kilometre Array Pathfinder…

Extremely flat and inverted radio spectra as observed in galactic nuclei and BL Lac sources are still a challenge for fast particle acceleration models. Continuous acceleration by electric fields in reconnection regions can result in almost…

Classifying large scale networks into several categories and distinguishing them according to their fine structures is of great importance with several applications in real life. However, most studies of complex networks focus on properties…

Radio spectrum monitoring in contested environments motivates the need for reliable automatic signal classification technology. Prior work highlights deep learning as a promising approach, but existing models depend on brute-force Doppler…

The state-of-the-art in semantic segmentation is currently represented by fully convolutional networks (FCNs). However, FCNs use large receptive fields and many pooling layers, both of which cause blurring and low spatial resolution in the…

Although Convolutional Neural Networks (CNNs) have achieved promising results in image classification, they still are vulnerable to affine transformations including rotation, translation, flip and shuffle. The drawback motivates us to…

Modern high-sensitivity radio telescopes are discovering an increased number of resolved sources with intricate radio structures and fainter radio emissions. These sources often present a challenge because source detectors might identify…

Deep learning algorithms offer a powerful means to automatically analyze the content of medical images. However, many biological samples of interest are primarily transparent to visible light and contain features that are difficult to…

Giant radio galaxies (GRGs) are physically large radio sources that extend well beyond their host galaxy environment. Their polarization properties are affected by the poorly constrained magnetic field that permeates the intergalactic…

We have obtained the polarization data cube of the VRO 42.05.01 supernova remnant at 1240 MHz using the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Three-dimensional Faraday Synthesis is applied to the FAST data to derive…

A claimed detection of cosmological tensor perturbations from inflation via B-mode polarization of the cosmic microwave background requires distinguishing other possible B-mode sources. One such potential source of confusion is primordial…

Considering the spatially separated polarization radiation and Faraday rotation regions to simulate complex interstellar media, we study synchrotron polarization gradient techniques' measurement capabilities. We explore how to trace the…

Optical neural networks are emerging as a powerful and versatile tool for processing optical signals directly in the optical domain with superior speed, integrability, and functionality. Their application to optical polarization enables…

Astrophysical images in the GeV band are challenging to analyze due to the strong contribution of the background and foreground astrophysical diffuse emission and relatively broad point spread function of modern space-based instruments. In…

This paper addresses the problem of depth estimation from a single still image. Inspired by recent works on multi- scale convolutional neural networks (CNN), we propose a deep model which fuses complementary information derived from…

We investigate the origin of the high Faraday rotation measures (RMs) found for polarized radio galaxies in clusters. The two most likely origins are, magnetic fields local to the source, or magnetic fields located in the foreground…

Out of the estimated few trillion galaxies, only around a million have been detected through radio frequencies, and only a tiny fraction, approximately a thousand, have been manually classified. We have addressed this disparity between…

The polarisation dynamics of nuclear spins weakly coupled to an NV center is highly sensitive to the parameters of the microwave control and the nuclear Larmor frequency. What is commonly regarded as a challenge, we propose here as a…

Most current semantic segmentation methods rely on fully convolutional networks (FCNs). However, their use of large receptive fields and many pooling layers cause low spatial resolution inside the deep layers. This leads to predictions with…

I/Q modulation classification is a unique pattern recognition problem as the data for each class varies in quality, quantified by signal to noise ratio (SNR), and has structure in the complex-plane. Previous work shows treating these…