@inproceedings{5d3deab3773c40768541a65a484c435c,
title = "Automated detection of galaxy groups through probabilistic hough transform",
abstract = "Galaxy groups play a significant role in explaining the evolution of the universe. Given the amounts of available survey data, automated discovery of galaxy groups is of utmost interest. We introduce a novel methodology, based on probabilistic Hough transform, for finding galaxy groups embedded in a rich background. The model takes advantage of a typical signature pattern of galaxy groups known as “fingersof-God”. It also allows us to include prior astrophysical knowledge as an inherent part of the method. The proposed method is first tested in large scale controlled experiments with 2-D patterns and then verified on 3-D realistic mock data (comparing with the well-known friends-of-friends method used in astrophysics). The experiments suggest that our methodology is a promising new candidate for galaxy group finders developed within a machine learning framework.",
keywords = "Galaxy group finder, Pattern Recognition, Probabilistic Hough transform",
author = "Ibrahem, {Rafee T.} and Peter Tino and Pearson, {Richard J.} and Ponman, {Trevor J.} and Arif Babul",
year = "2015",
doi = "10.1007/978-3-319-26555-1_37",
language = "English",
isbn = "9783319265544",
volume = "9491",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "323--331",
editor = "Sabri Arik and Tingwen Huang and Lai, {Weng Kin} and Lui, {Qingshan }",
booktitle = "Neural Information Processing",
note = "22nd International Conference on Neural Information Processing, ICONIP 2015 ; Conference date: 09-11-2015 Through 12-11-2015",
}