Abstract Machine learning (automated processes that learn by example in order to classify,
predict, discover, or generate new data) and artificial intelligence (methods by which a …

Since the beginning of the 21st century, the fields of astronomy and astrophysics have
experienced significant growth at observational and computational levels, leading to the …

Spectroscopic surveys require fast and efficient analysis methods to maximize their scientific
impact. Here, we apply a deep neural network architecture to analyse both SDSS-III …

Classification is valuable and necessary in spectral analysis, especially for data-driven
mining. Along with the rapid development of spectral surveys, a variety of classification …

Numerous ongoing and future large area surveys (eg Dark Energy Survey, EUCLID, Large
Synoptic Survey Telescope, Wide Field Infrared Survey Telescope) will increase by several …

Next-generation large sky surveys will observe up to billions of galaxies for which basic
structural parameters are needed to study their evolution. This is a challenging task that, for …

Near-infrared (NIR) spectroscopy has been widely utilized to predict multi-constituents of
corn in agriculture. However, directly extracting constituent information from the NIR spectra …

Resolving the phase structure of neutral hydrogen (H i) is crucial for understanding the life
cycle of the interstellar medium (ISM). However, accurate measurements of H i temperature …

Discovering pulsars is a significant and meaningful research topic in the field of radio
astronomy. With the advent of astronomical instruments, the volume and rate of data …

Developing a robust deep neural network (DNN) for a specific task is not only time-
consuming but also requires lots of experienced human experts. In order to make deep …