Related papers: AGN selection in the AKARI NEP deep field with the…

Most existing fuzzy set methods use points as their input, which is the finest granularity from the perspective of granular computing. Consequently, these methods are neither efficient nor robust to label noise. Therefore, we propose a…

We present a highly complete and reliable mid-infrared (MIR) colour selection of luminous AGN candidates using the 3.4, 4.6, and 12 um bands of the WISE survey. The MIR colour wedge was defined using the wide-angle Bright Ultra-Hard…

We present the results of a program to identify so far unknown active nuclei (AGN) in galaxies. Candidate galactic nuclei have been selected for optical spectroscopy from a cross-correlation of the ROSAT all sky survey (RASS) bright source…

This is the first paper in a dedicated series to study the properties of the optically selected BLR-less AGNs (Active Galactic Nuclei with no-hidden central broad emission line regions). We carried out a systematic search for the BLR-less…

Reliably identifying active galactic nuclei (AGNs) in dwarf galaxies is key to understanding black hole demographics at low masses and constraining models for black hole seed formation. Here we present Chandra X-ray Observatory observations…

Measuring the redshift of active galactic nuclei (AGNs) requires the use of time-consuming and expensive spectroscopic analysis. However, obtaining redshift measurements of AGNs is crucial as it can enable AGN population studies, provide…

Classifying catalog objects as stars, galaxies, or AGN is a crucial part of any statistical study of galaxies. We describe our pipeline for binary (star/galaxy) and multiclass (star/galaxy/Type I AGN/Type II AGN) classification developed…

The combination of neural network and fuzzy systems into neuro-fuzzy systems integrates fuzzy reasoning rules into the connectionist networks. However, the existing neuro-fuzzy systems are developed under shallow structures having lower…

We demonstrate the use of the AKARI survey photometric data in the study of galactic star formation. Our aim was to select young stellar objects (YSOs) in the AKARI FIS catalogue. We used AKARI Far-Infrared Surveyor and Wide-field Infrared…

Generative Adversarial Networks (GANs) are well-known tools for data generation and semi-supervised classification. GANs, with less labeled data, outperform Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) in…

The Wide Field X-ray Telescope (WFXT) will provide tens of millions of AGN, with more than 4x10^5 expected at z>3. Here we review the issues present in the identification of (large) samples of faint and high-redshift X-ray sources, and…

Computing photo-z for AGN is challenging, primarily due to the interplay of relative emissions associated with the SMBH and its host galaxy. SED fitting methods, effective in pencil-beam surveys, face limitations in all-sky surveys with…

Machine Learning methods have extensively evolved to support industrial big data methods and their corresponding need in gas turbine maintenance and prognostics. However, most unsupervised methods need extensively labeled data to perform…

Extended Kalman Filter (EKF) has been a popular approach to localization a mobile robot. However, the performance of the EKF and the quality of the estimation depends on the correct a priori knowledge of process and measurement noise…

We develop and demonstrate a classification system constituted by several Support Vector Machines (SVM) classifiers, which can be applied to select quasar candidates from large sky survey projects, such as SDSS, UKIDSS, GALEX. How to…

We present a study of galaxies showing mid-infrared variability in the deepest Spitzer/MIPS 24 $\mu$m surveys in the GOODS-South field. We divide the dataset in epochs and subepochs to study the long-term (months-years) and the short-term…

X-rays offer a reliable method to identify Active Galactic Nuclei (AGN). However, in the high-redshift Universe X-ray AGN are poorly sampled due to their relatively low space density and the small areas covered by X-ray surveys. In addition…

A major limitation of fuzzy or neuro-fuzzy systems is their failure to deal with high-dimensional datasets. This happens primarily due to the use of T-norm, particularly, product or minimum (or a softer version of it). Thus, there are…

We present a census of local active galactic nuclei (AGN) at a redshift of $z\leq0.025$ selected using the high-ionization [Ne v] $\lambda14.32\,\mu$m emission line from the Infrared Database of Extragalactic Observables from Spitzer…

We classify the spectral energy distributions (SEDs) of 431,038 sources in the 9 sq. deg Bootes field of the NOAO Deep Wide-Field Survey (NDWFS). There are up to 17 bands of data available per source, including ultraviolet (GALEX), optical…