相关论文: Radio Sources Segmentation and Classification with…
Hybrid Morphology Radio Sources (HyMoRS) are a very rare subclass of radio galaxies with apparent mixed FR morphology, i.e. these galaxies seem to have an FR-I structure on one side of the core and an FR-II structure on the other side of…
Indoor scenes are usually characterized by scattered objects and their relationships, which turns the indoor scene classification task into a challenging computer vision task. Despite the significant performance boost in classification…
While Supernova Remnants (SNRs) are widely considered the primary accelerators of cosmic rays (CRs) up to hundreds of TeV, they struggle to account for the CR flux at PeV energies, suggesting the existence of additional PeVatrons.…
There are various automotive applications that rely on correctly interpreting point cloud data recorded with radar sensors. We present a deep learning approach for histogram-based processing of such point clouds. Compared to existing…
Nuclear segmentation is an important step for profiling aberrant regions of histology sections. However, segmentation is a complex problem as a result of variations in nuclear geometry (e.g., size, shape), nuclear type (e.g., epithelial,…
PURPOSE: This study aimed to develop a deep learning-based tool to detect and localize lung nodules with chest radiographs(CXRs). We expected it to enhance the efficiency of interpreting CXRs and reduce the possibilities of delayed…
We present here the results of a 325 MHz radio survey of M31, conducted with the A-configuration of the Very Large Array. The survey covered an area of 7.6 deg$^2$, and a total of 405 radio sources between $\la$6\arcsec and 170\arcsec in…
We have carried out extensive radio and optical follow-up of 176 sources from the 15 GHz 9th Cambridge survey. Optical identifications have been found for 155 of the radio sources; optical images are given with radio maps overlaid. The…
In the field of transmission electron microscopy, data interpretation often lags behind acquisition methods, as image processing methods often have to be manually tailored to individual datasets. Machine learning offers a promising approach…
Identifying high-emission vehicles is a crucial step in regulating urban pollution levels and formulating traffic emission reduction strategies. However, in practical monitoring data, the proportion of high-emission state data is…
We present the catalog of Radio sources associated with Optical Galaxies and having Unresolved or Extended morphologies I (ROGUE~I), consisting of 32,616 spectroscopically selected galaxies. It is the largest handmade catalog of this kind,…
$\mbox{H}$ $\mbox{I}$ 21-cm absorption, an extremely useful tool to study the cold atomic hydrogen gas, can arise either from the intervening galaxies along the line-of-sight towards the background radio source or from the radio source…
In this paper we present the optical, near-infrared (NIR) and X-ray identifications of the 6287 radio sources detected in the 2.1 GHz deep radio survey down to a median rms of ~ 41microJy/beam obtained with the Australia Telescope Compact…
Audio-Visual Learning (AVL) is one fundamental task of multi-modality learning and embodied intelligence, displaying the vital role in scene understanding and interaction. However, previous researchers mostly focus on exploring downstream…
The Evolutionary Map of the Universe (EMU) large-area radio continuum survey will detect tens of millions of radio galaxies, giving an opportunity for the detection of previously unknown classes of objects. To maximise the scientific value…
Diffuse radio emission in galaxy clusters, such as radio halos, relics, and mini halos, is a key tracer of non-thermal processes, turbulence, and magnetic fields within the intra-cluster medium. However, their low surface brightness, as…
We study the problem of source separation for music using deep learning with four known sources: drums, bass, vocals and other accompaniments. State-of-the-art approaches predict soft masks over mixture spectrograms while methods working on…
Traditionally, fast radio transient searches are conducted on dedispersed time series using thresholding techniques based on the statistical properties of the data. However, peaks in dedispersed time series do not directly provide…
Next-generation cellular concepts rely on the processing of large quantities of radio-frequency (RF) samples. This includes Radio Access Networks (RAN) connecting the cellular front-end based on software defined radios (SDRs) and a…
Source classifications, stellar masses and star formation rates are presented for 80,000 radio sources from the first data release of the Low Frequency Array Two-metre Sky Survey (LoTSS) Deep Fields, which represents the widest deep radio…