D. Matveev | Searcharxiv

arXiv2026

Website with interactive visualization of multivariate astronomical time series

Light curves represent astronomical time series of flux measured across one or more photometric bands. With the rapid growth of large-scale sky surveys, time-domain astronomy has become an essential area of modern astrophysical research. Interactive visualization of extensive light-curve datasets plays a key role in exploring transient phenomena and in planning large follow-up campaigns. In this work, we introduce two web-based platforms designed for interactive light-curve visualization: Fulu, for transient event studies, and VALC, for investigations of low-mass active galactic nuclei (AGNs). These tools provide a user-friendly interface for examining, comparing, and interpreting vast collections of astronomical light curves, supporting scientific discovery.

astro-ph.IM↗

arXiv2020

Vanishing Point Detection with Direct and Transposed Fast Hough Transform inside the neural network

In this paper, we suggest a new neural network architecture for vanishing point detection in images. The key element is the use of the direct and transposed Fast Hough Transforms separated by convolutional layer blocks with standard activation functions. It allows us to get the answer in the coordinates of the input image at the output of the network and thus to calculate the coordinates of the vanishing point by simply selecting the maximum. Besides, it was proved that calculation of the transposed Fast Hough Transform can be performed using the direct one. The use of integral operators enables the neural network to rely on global rectilinear features in the image, and so it is ideal for detecting vanishing points. To demonstrate the effectiveness of the proposed architecture, we use a set of images from a DVR and show its superiority over existing methods. Note, in addition, that the proposed neural network architecture essentially repeats the process of direct and back projection used, for example, in computed tomography.

cs.CV↗