80 citations · 391 across the 26 of their papers we have counts for
26 papers
Study of star clusters in the M83 galaxy with a convolutional neural network
J. Bialopetravičius, D. Narbutis
We present a study of evolutionary and structural parameters of star cluster candidates in the spiral galaxy M83. For this we use a convolutional neural network trained on mock clu…
Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincaré Embeddings
Lucia Larise Stavarache, Donatas Narbutis, Toyotaro Suzumura +2
In the recent years money laundering schemes have grown in complexity and speed of realization, affecting financial institutions and millions of customers globally. Strengthened pr…
Deriving star cluster parameters with convolutional neural networks. II. Extinction and cluster/background classification
J. Bialopetravičius, D. Narbutis
Context. Convolutional neural networks (CNNs) have been established as the go-to method for fast object detection and classification on natural images. This opens the door for astr…
Deriving star cluster parameters with convolutional neural networks. I. Age, mass, and size
J. Bialopetravičius, D. Narbutis, V. Vansevičius
Context. Convolutional neural networks (CNNs) have been proven to perform fast classification and detection on natural images and have potential to infer astrophysical parameters o…
Structural Parameters of Star Clusters: Signal to Noise Effects
D. Narbutis, A. Bridžius, D. Semionov
We study the impact of photometric signal to noise on the accuracy of derived structural parameters of unresolved star clusters using MCMC model fitting techniques. Star cluster im…
Deriving physical parameters of unresolved star clusters IV. The M33 star cluster system
P. de Meulenaer, D. Narbutis, T. Mineikis +1
Context. When trying to derive the star cluster physical parameters of the M33 galaxy using broad-band unresolved ground-based photometry, previous studies mainly made use of simpl…