STAR-GALAXY CLASSIFICATION USING MACHINE LEARNING ALGORITHMS AND DEEP LEARNING

被引:0
|
作者
Savyanavar, Amit Sadanand [1 ]
Mhala, Nikhil [1 ]
Sutar, Shiv H. [1 ]
机构
[1] Dr Vishwanath Karad MIT World Peace Univ, Sch Comp Engn & Technol, Pune, India
关键词
Cosmology; star-galaxy classification; Machine Learning; Convolution Neural Network;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cosmology is the study of the universe comprising stars and galaxies. Advancement in the telescope has made it possible to capture high -resolution images, which can be analysed using machine learning (ML) algorithms. This paper classifies the star galaxy dataset into two classes: star and galaxy using ML algorithms and compares their classification performance. It is observed that random forest provides better accuracy of 78% as compared to other ML classifiers. Further to improve the classification accuracy, we proposed a CNN (Convolution Neural Network) model and achieved an accuracy of 92.44%. Since the CNN model itself extracts the characteristics, it exhibits superior classification accuracy.
引用
收藏
页码:87 / 96
页数:10
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