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Classification of Galaxy Images Using Computer Vision and Artificial Neural Network Techniques: A Survey

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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) (AICV 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1377))

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Abstract

The automatic classification of the galaxies in our universe is one of the major challenges astronomers faces. Today, advances in computer vision and artificial neural network techniques can be used to tackle this problem. The main contribution of the paper aims to (i) discuss the different classification algorithms of galaxies, which is a step required for the subsequent scientific analyses, (ii) present the classifiers of machine learning (ML) that can be used in conjunction with conventional methods that use explicit modeling, and (iii) summarize the latest computer vision efforts, especially neural networks (NNs) and their variants which classify galaxy images automatically. Multilayer perceptron (MLP) classifier outperforms all others in all scenarios performance accuracy achieved 99.5278%.

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Correspondence to Ibrahim Yasser .

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El-Khalek, A.A.A., Khalil, A.T., El-Soud, M.A.A., Yasser, I. (2021). Classification of Galaxy Images Using Computer Vision and Artificial Neural Network Techniques: A Survey. In: Hassanien, A.E., et al. Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021). AICV 2021. Advances in Intelligent Systems and Computing, vol 1377. Springer, Cham. https://doi.org/10.1007/978-3-030-76346-6_30

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