Related papers: AGN selection in the AKARI NEP deep field with the…
To improve the problem that the parameter identification for fuzzy neural network has many time complexities in calculating, an improved T-S fuzzy inference method and an parameter identification method for fuzzy neural network are…
We have constructed a catalog of active galactic nuclei (AGNs) with $z < 0.13$, based on optical spectroscopy, from the parent sample of galaxies in the 6dF galaxy survey (Final Release of 6dFGS), a census of the Southern hemisphere. This…
The approach described here allows to use the fuzzy Object Based Representation of imprecise and uncertain knowledge. This representation has a great practical interest due to the possibility to realize reasoning on classification with a…
This paper presents a genetic stereo matching algorithm with fuzzy evaluation function. The proposed algorithm presents a new encoding scheme in which a chromosome is represented by a disparity matrix. Evolution is controlled by a fuzzy…
We present a highly reliable and efficient mid-infrared colour-based selection technique for luminous active galactic nuclei (AGN) using the Wide-field Infrared Survey Explorer (WISE) survey. Our technique is designed to identify objects…
Context. Active galactic nuclei (AGN) of galaxies play an important role in the life and evolution of galaxies due to the impact they exert on certain properties and the evolutionary path of galaxies. It is well known that infrared (IR)…
The density-based clustering algorithm DBSCAN has been applied to the Fermi Large Area Telescope (LAT) dataset of $ E_{\gamma} \geqslant 100$ GeV events with $\lvert b\rvert>10^{\circ}$, in order to search for new very high energy (VHE)…
Submillimetre-selected galaxies (SMGs) at high redshift ($z$ $\sim$ 2) are potential host galaxies of active galactic nuclei (AGN). If the local Universe is a good guide, $\sim$ 50$\%$ of the obscured AGN amongst the SMG population could be…
We introduce a new infrared diagnostic to separate galaxies on the basis of their dominant infrared emission: stellar or nuclear. The main novelty with respect to existing diagnostics, is the usage of a broad band encompassing at the same…
We discuss a new method for unveiling the possible blazar AGN nature among the numerous population of Unassociated Gamma-ray sources (UGS) in the Fermi catalogues. Our tool relies on positional correspondence of the Fermi object with X-ray…
Deep neural networks (DNN) have been used successfully in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging due to their poor interpretability. In this paper, we…
To ensure the reliability of DNN systems and address the test generation problem for neural networks, this paper proposes a fuzzing test generation technique based on many-objective optimization algorithms. Traditional fuzz testing employs…
This paper describes the design and development of a prototype technique for artificial intelligence based on the fusion of genetic algorithm, neural network and fuzzy logic. It starts by establishing a relationship between the neural…
Photo-realistic modeling and rendering of fuzzy objects with complex opacity are critical for numerous immersive VR/AR applications, but it suffers from strong view-dependent brightness, color. In this paper, we propose a novel scheme to…
Active Galactic Nuclei (AGNs) are characterized by emission of radiation over more than 10 orders of magnitude in frequency. Therefore, the execution of extensive surveys of the sky, with different types of detectors, is providing the…
To investigate the population of massive black holes in dwarf galaxies, we conduct a systematic search for active galactic nuclei (AGNs) using data from the first data release of the eROSITA All-Sky Survey (eRASS1). We crossmatch dwarf…
Recently, convolution neural networks (CNNs) have attracted a great deal of attention due to their remarkable performance in various domains, particularly in image and text classification tasks. However, their application to tabular data…
We outline a strategy to select faint (i<24.5) type 1 AGN candidates down to the Seyfert/QSO boundary for spectroscopic targeting in the COSMOS field, picking candidates by their nonstellar colors in broadband ground-based photometry and…
Machine learning methods are increasingly helping astronomers identify new radio pulsars. However, they require a large amount of labelled data, which is time consuming to produce and biased. Here we describe a Semi-Supervised Generative…
With the advent of GRAVITY+, the upgrade to the beam combiner GRAVITY at the Very Large Telescope Interferometer (VLTI), fainter and higher redshift active galactic nuclei (AGNs) are becoming observable, opening an unprecedented opportunity…