Related papers: Radio U-Net: a convolutional neural network to det…
Despite the growing number of gamma-ray sources detected by Fermi-LAT, about one third of the sources in each survey remains of uncertain type. We present a new deep neural network approach for the classification of unidentified or…
Given the incomplete sampling of spatial frequencies by radio interferometers, achieving precise restoration of astrophysical information remains challenging. To address this ill-posed problem, compressive sensing(CS) provides a robust…
Identifying the positions of granular particles from experimental images is often complicated by their partial overlap in two dimensional projections. Uneven backgrounds and inhomogeneous illuminations can add to the challenge. Conventional…
We propose AuralNet, a novel 3D multi-source binaural sound source localization approach that localizes overlapping sources in both azimuth and elevation without prior knowledge of the number of sources. AuralNet employs a gated…
The advancements in deep learning technologies have produced immense contributions to biomedical image analysis applications. With breast cancer being the common deadliest disease among women, early detection is the key means to improve…
A multitude of imaging and vision tasks have seen recently a major transformation by deep learning methods and in particular by the application of convolutional neural networks. These methods achieve impressive results, even for…
Radio halos are diffuse, extended sources of radio emission detected primarily in massive, merging galaxy clusters. In smaller and/or relaxed clusters, where no halos are detected, one can instead place upper limits to a possible radio…
Objective: The accurate segmentation of capnograms during cardiopulmonary resuscitation (CPR) is essential for effective patient monitoring and advanced airway management. This study aims to develop a robust algorithm using a U-net…
Distributed Acoustic Sensing (DAS) that transforms city-wide fiber-optic cables into a large-scale strain sensing array has shown the potential to revolutionize urban traffic monitoring by providing a fine-grained, scalable, and…
This study investigates the effectiveness of U-Net architectures integrated with various convolutional neural network (CNN) backbones for automated lung cancer detection and segmentation in chest CT images, addressing the critical need for…
Background: Breast and thyroid cancers pose an increasing public-health burden. Ultrasound imaging is a cost-effective, real-time modality for lesion detection and segmentation, yet suffers from speckle noise, overlapping structures, and…
Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…
In image fusion tasks, images obtained from different sources exhibit distinct properties. Consequently, treating them uniformly with a single-branch network can lead to inadequate feature extraction. Additionally, numerous works have…
Deep convolutional neural networks have been proven to be very effective in image related analysis and tasks, such as image segmentation, image classification, image generation, etc. Recently many sophisticated CNN based architectures have…
An ultraviolet survey of M31 has been carried out during 2017-23 with the UVIT instrument onboard the AstroSat Observatory. Here we present far and near ultraviolet (FUV and NUV) observations from the M31 UVIT survey, which covers a sky…
Sea-land segmentation is an important process for many key applications in remote sensing. Proper operative sea-land segmentation for remote sensing images remains a challenging issue due to complex and diverse transition between sea and…
Context: Diffuse radio emission, in the form of radio halos and relics, traces regions in clusters with shocks or turbulence, probably produced by cluster mergers. Some models of diffuse radio emission in clusters indicate that virtually…
Among astrophysical sources in the Advanced LIGO and Advanced Virgo detectors' frequency band are rotating non-axisymmetric neutron stars emitting long-lasting, almost-monochromatic gravitational waves. Searches for these continuous…
The continuum emission from 1 to 2 GHz of The HI/OH/Recombination line survey of the inner Milky Way (THOR) at $\lesssim$18" resolution covers $\sim 132$ square degrees of the Galactic plane and detects 10387 sources. Similarly, the first…
Enhancing the sound quality of historical music recordings is a long-standing problem. This paper presents a novel denoising method based on a fully-convolutional deep neural network. A two-stage U-Net model architecture is designed to…