相关论文: Radio Sources Segmentation and Classification with…

Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedious and often leads to a disagreement between pathologists.…

We present BlendHunter, a proof-of-concept for a deep transfer learning based approach for the automated and robust identification of blended sources in galaxy survey data. We take the VGG-16 network with pre-trained convolutional layers…

The LOw Frequency ARray Two-metre Sky Survey second data release (LoTSS DR2) covers 27\% of the northern sky and contains around four million radio sources. The development of this catalogue involved a large citizen science project (Radio…

We present the results of Giant Metrewave Radio Telescope (GMRT) observations to detect H{\sc i} in absorption towards the cores of a sample of radio galaxies. From observations of a sample of 16 sources, we detect H{\sc i} in absorption…

A method for reconstructing the direction of a fast neutron source using a segmented organic scintillator-based detector and deep learning model is proposed and analyzed. The model is based on recurrent neural network, which can be trained…

The work of a single musician, group or composer can vary widely in terms of musical style. Indeed, different stylistic elements, from performance medium and rhythm to harmony and texture, are typically exploited and developed across an…

We have performed new 1.4 GHz and 5 GHz observations of the Local Group galaxy M33 with the Jansky Very Large Array. Our survey has a limiting sensitivity of 20 uJy (4-sigma) and a resolution of 5.9 arcsec (FWHM), corresponding to a spatial…

Since radio sources with Ultra Steep Spectra (USS; alpha <~ -1.30; S ~ nu^alpha) are efficient tracers of high redshift radio galaxies (HzRGs), we have defined three samples of such USS sources using the recently completed WENSS, TEXAS,…

Machine learning approaches to auditory object recognition are traditionally based on engineered features such as those derived from the spectrum or cepstrum. More recently, end-to-end classification systems in image and auditory…

We have used the Very Large Array (VLA) to conduct a survey for radio continuum emission in the sample of 52 Seyfert nuclei selected from the optical spectroscopic galaxy catalog of Ho, Filippenko, and Sargent. This Seyfert sample is the…

In this study, we present an interpretable deep learning framework for the early detection of breast cancer using quantitative features extracted from digitized fine needle aspirate (FNA) images of breast masses. Our deep neural network,…

The third data release of the LOFAR Two-metre Sky Survey provides an unprecedented view of the northern sky at 144 MHz. While compact sources can be efficiently identified with automated software packages, the detection of diffuse radio…

The objective of deep learning methods based on encoder-decoder architectures for music source separation is to approximate either ideal time-frequency masks or spectral representations of the target music source(s). The spectral…

The rapid increase in serendipitous X-ray source detections requires the development of novel approaches to efficiently explore the nature of X-ray sources. If even a fraction of these sources could be reliably classified, it would enable…

We study lepton-flavor-violating (LFV) decays of a heavy Higgs boson, $H \to \mu\tau$, in the Type-III two-Higgs-doublet model by recasting the CMS search at $\sqrt{s} = 13$ TeV with 35.9 fb$^{-1}$ using fast detector simulation in the mass…

We present the first results from a pilot study to search for distant radio galaxies in the southern hemisphere (delta < -32). Within a 360 deg^2 region of sky, we define a sample of 76 ultra-steep spectrum (USS) radio sources from the 843…

Digital pathology has recently been revolutionized by advancements in artificial intelligence, deep learning, and high-performance computing. With its advanced tools, digital pathology can help improve and speed up the diagnostic process,…

We present ATCA observations of the H2O maser line and radio continuum at 18.0GHz and 22.8GHz, toward a sample of 192 massive star forming regions containing several clumps already imaged at 1.2mm. The main aim of this study is to…

Accurate segmentation of gross tumor volume (GTV) is essential for effective MRI-guided adaptive radiotherapy (MRgART) in head and neck cancer. However, manual segmentation of the GTV over the course of therapy is time-consuming and prone…

Blazars are among the most studied sources in high-energy astrophysics as they form the largest fraction of extragalactic gamma-ray sources and are considered prime candidates for being the counterparts of high-energy astrophysical…