Machine learning search for gamma-ray burst afterglows in optical images

Thanks to the rapid advances in robotic telescopes and wide field surveys, the time domain astronomy reveals a huge number of transient detections every night. Therefore, automatic classification of sources in the optical images is essential. A special attention is brought to the identification of gamma-ray burst afterglows using the combined observational data from the GROND telescope and the SDSS survey. Their successful identification can lead to further follow-up observations by dedicated telescopes and for statistical studies of these transients.