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Home > Intelligent Astrophysics > Periodic Astrometric Signal Recovery Through Convolutional Autoencoders
Intelligent Astrophysics |
Ivan Zelinka; Massimo Brescia; Dalya Baron
Springer International Publishing
Intelligent Astrophysics
Periodic Astrometric Signal Recovery Through Convolutional Autoencoders
Authors

Michele Delli Veneri; Louis Desdoigts; Morgan A. Schmitz; Alberto Krone-Martins; Emille E. O. Ishida; Peter Tuthill et al.

ARI Id

1665313109406_5854626

Access

Not Available Free

Pages

167-195

DOI

10.1007/978-3-030-65867-0_8

Chapter URL

https://rd.springer.com/chapter/10.1007/978-3-030-65867-0_8

Table of Contents of Book
Showing 1 to 14 of 14 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
i-viii
Artificial Intelligence in Astrophysics
Ivan Zelinka; Thanh Cong Truong; Diep Quoc Bao; Lumir Kojecky; Eslam Amer
1-28
The Complexity and Information Content of Simulated Universes
Franco Vazza
29-56
The Voronoi Tessellation Method in Astronomy
Iryna Vavilova; Andrii Elyiv; Daria Dobrycheva; Olga Melnyk
57-79
Statistical Characterization and Classification of Astronomical Transients with Machine Learning in the era of the Vera C. Rubin Observatory
Marco Vicedomini; Massimo Brescia; Stefano Cavuoti; Giuseppe Riccio; Giuseppe Longo
81-113
Application of Machine and Deep Learning Methods to the Analysis of IACTs Data
Alessandro Bruno; Antonio Pagliaro; Valentina La Parola
115-136
Intelligent Photometric Identification of Extragalactic Objects from AllWISE \(\times \) Pan-STARRS DR1 Data
Vladislav Khramtsov; Volodymyr Akhmetov; Peter Fedorov; Sergii Khlamov; Artem Dmytrenko; Anna Velichko
137-152
Ensemble Classifiers for Pulsar Detection
Jakub Holewik; Gerald Schaefer
153-166
Periodic Astrometric Signal Recovery Through Convolutional Autoencoders
Michele Delli Veneri; Louis Desdoigts; Morgan A. Schmitz; Alberto Krone-Martins; Emille E. O. Ishida; Peter Tuthill et al.
167-195
Comparison of Outlier Detection Methods on Astronomical Image Data
Lars Doorenbos; Stefano Cavuoti; Massimo Brescia; Antonio D’Isanto; Giuseppe Longo
197-223
Anomaly Detection in Astrophysics: A Comparison Between Unsupervised Deep and Machine Learning on KiDS Data
Maurizio D’Addona; Giuseppe Riccio; Stefano Cavuoti; Crescenzo Tortora; Massimo Brescia
225-244
Rejection Criteria Based on Outliers in the KiDS Photometric Redshifts and PDF Distributions Derived by Machine Learning
Valeria Amaro; Stefano Cavuoti; Massimo Brescia; Giuseppe Riccio; Crescenzo Tortora; Maurizio D’Addona et al.
245-264
Large Astronomical Time Series Pre-processing for Classification Using Artificial Neural Networks
David Andrešič; Petr Šaloun; Bronislava Pečíková
265-293
Back Matter
295-296
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 14 of 14 entries
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