Radio galaxies classification system using machine learning techniques in the IoT Era-Reference-Cited by-同舟云学术

Radio galaxies classification system using machine learning techniques in the IoT Era

Published:2022-06-08 Issue: Volume: Page:1-13
ISSN:0952-813X
Container-title:Journal of Experimental & Theoretical Artificial Intelligence
language:en
Short-container-title:Journal of Experimental & Theoretical Artificial Intelligence

Author:

Dimililer Kamil¹^ORCID,Teimourian Hanifa²,Al-Turjman Fadi³

Affiliation:

1. Electrical and Electronic Engineering, International Research Centre for AI and IoT, Applied Artificial Intelligence Research Centre (AAIRC), Near East University, Nicosia, North Cyprus, Turkey

2. Electrical and Electronic Engineering, International Research Centre for AI and IoT, Near East University, Nicosia, North Cyprus, Turkey

3. Artificial Intelligence Engineering, International Research Centre for AI and IoT, AI and Robotics Institute, Near East University, Nicosia, North Cyprus, Turkey

Publisher

Informa UK Limited

Subject

Artificial Intelligence,Theoretical Computer Science,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2022.2080277

Reference47 articles.

1. Radio Galaxy Zoo: machine learning for radio source host galaxy cross-identification

2. Classifying Radio Galaxies with the Convolutional Neural Network

3. Bird, J., Colburn, K., Petzold, L. & Lubin, P. (2020). Model optimization for deep space exploration via simulators and deep learning arXiv preprint arXiv:2012.14092. https://doi.org/10.48550/arXiv.2012.14092

4. Breaking the hierarchy of galaxy formation

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