Related papers: Artificial Neural Network based gamma-hadron segre…
In the quest for low power, bio-inspired computation both memristive and memcapacitive-based Artificial Neural Networks (ANN) have been the subjects of increasing focus for hardware implementation of neuromorphic computing. One step…
The IceCube Neutrino Observatory is a cubic-kilometer detector located in the Antarctic ice at the geographic South Pole. It reads out over 5,000 photomultiplier tubes (PMTs) to detect Cherenkov light produced by secondary particles,…
Graph Neural Networks(GNNs) are a family of neural models tailored for graph-structure data and have shown superior performance in learning representations for graph-structured data. However, training GNNs on large graphs remains…
The ``Gamma Ray Astronomy at ALmeria'' (GRAAL) experiment uses 63 heliostat-mirrors with a total mirror area of ~ 2500 m2 from the CESA-1 field to collect Cherenkov light from airshowers. The detector is located in a central solar tower and…
In order to develop a pipeline for automated classification of stars to be observed by the TAUVEX ultraviolet space Telescope, we employ an artificial neural network (ANN) technique for classifying stars by using synthetic spectra in the UV…
A new ground-based wide-field extensive air shower array known as the High-Altitude Water Cherenkov (HAWC) Observatory promises a new window to monitoring the $\sim$100 GeV gamma-ray sky with the potential for detecting a high energy…
Multi-dimensional data classification is an important and challenging problem in many astro-particle experiments. Neural networks have proved to be versatile and robust in multi-dimensional data classification. In this article we shall…
A sample of selected active galactic nuclei (AGN) was observed in 2003 and 2004 with the High Energy Stereoscopic System (H.E.S.S.), an array of imaging atmospheric-Cherenkov telescopes in Namibia. The redshifts of these candidate…
This study reports grain boundary (GB) energy calculations for 46 symmetric-tilt GBs in alpha-iron using molecular mechanics based on an artificial neural network (ANN) potential and compares the results with calculations based on the…
We present a provable, sampling-based approach for generating compact Convolutional Neural Networks (CNNs) by identifying and removing redundant filters from an over-parameterized network. Our algorithm uses a small batch of input data…
The window of TeV Gamma-Ray Astrophysics was opened less than two decades ago, when the Crab Nebula was detected for the first time. After several years of development, the technique used by imaging atmospheric Cherenkov telescopes like…
Context. We are operating an elastic LIDAR for the monitoring of atmospheric conditions during regular observations of the MAGIC Telescopes. Aims. We present and evaluate methods to convert aerosol extinction profiles, obtained with the…
When very-high-energy gamma rays interact high in the Earth's atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into…
In recent years, Imaging Atmospheric Cherenkov Telescopes (IACTs) have discovered a rich diversity of very high energy (VHE, > 100 GeV) gamma-ray emitters in the sky. These instruments image Cherenkov light emitted by gamma-ray induced…
It is a challenge to segment the location and size of rectal cancer tumours through deep learning. In this paper, in order to improve the ability of extracting suffi-cient feature information in rectal tumour segmentation, attention…
In this work, we propose a graph-adaptive pruning (GAP) method for efficient inference of convolutional neural networks (CNNs). In this method, the network is viewed as a computational graph, in which the vertices denote the computation…
This paper describes an efficient rule generation algorithm, called rule generation from artificial neural networks (RGANN) to generate symbolic rules from ANNs. Classification rules are sought in many areas from automatic knowledge…
Automated segmentation of the optic cup and disk on retinal fundus images is fundamental for the automated detection / analysis of glaucoma. Traditional segmentation approaches depend heavily upon hand-crafted features and a priori…
Gamma rays with energies greater than 7 TeV from the Crab pulsar/nebula have been observed at large zenith angles, using the Imaging Atmospheric Technique from Woomera, South Australia. CANGAROO data taken in 1992, 1993 and 1995 indicate…
Deep Neural Network (DNN) based point cloud semantic segmentation has presented significant achievements on large-scale labeled aerial laser point cloud datasets. However, annotating such large-scaled point clouds is time-consuming. Due to…