ExoSGAN and ExoACGAN: Exoplanet Detection Using Adversarial Training Algorithms - Astrobiology

Exoplanet detection opens the door to the discovery of new habitable worlds and helps us understand how planets were formed. With the objective of finding earth-like habitable planets, NASA launched Kepler space telescope and its follow up mission K2. The advancement of observation capabilities has increased the range of fresh data available for research, and manually handling them is both time-consuming and difficult. Machine learning and deep learning techniques can greatly assist in lowering human efforts to process the vast array of data produced by the modern instruments of these exoplanet programs in an economical and unbiased manner. However, care should be taken to detect all the exoplanets precisely while simultaneously minimizing the misclassification of non-exoplanet stars.