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Research Article
Determination of Metallicity of different Galaxies using Image Processing and DeepLearning Algorithms
Aryan Raj Tiwary1
Aditya Kumar Gupta2
Preetish Niket3
Tapas Khanijo4
Dr. Jyoti Gupta5
12345Electronics and Communication Engineering, Bharati Vidyapeeth’s College of Engineering, New Delhi, India.
Published Online: July-August 2022
Pages: 194-199
Cite this article
No DOIReferences
[1]. Sparke, L. S.; Gallagher, J. S. III (2000). Galaxies in the Universe: An Introduction. Cambridge University Press. ISBN 978-0-521-59740-
1.
[2]. Wheeler, J. Craig; Sneden, Christopher (1989). Abundance Ratios as a Function of Metallicity. Annual Review of Astronomy and
Astrophysics, 27(1), 279– 349.
[3]. John F Wu, Steven Boada, Using Convolutional Neural Networks To Predict Galaxy Metallicity From Three-Color Images, Monthly
Notices Of The Royal Astronomical Society, Volume 484, Issue 4, April 2019, Pages 4683–4694.
[4]. Wu, John F.“Deep Learning With Galaxy Images.”GitHub,
jwuphysics.github.io/blog/galaxies/astrophysics/deep%20learning/computer%20vision/2020/05/21/exploring-galaxies-with-deep-learning.html.
[5]. Lacy, M., Riley, J. M., Waldram, E. M., McMahon, R. G., & Warner, P. J. (1995). "A radio-optical survey of the North Ecliptic CAP".
Monthly Notices of the Royal Astronomical Society. 276 (2): 614–626.
[6]. Dieleman S., Willett K. W., Dambre J., 2015, Monthly Notices of the Royal Astronomical Society, 450, 1441. [7]. Huertas-Company M., et
al., 2015, The Astrophysical Journal Supplemnent Series, 221, 8.
[8]. Beck M. R., et al., 2018, Monthly Notices of the Royal Astronomical Society, 476, 5516.[9]. Hocking A., Geach J. E., Sun Y., Davey N., 2018, Monthly Notices of the Royal Astronomical Society, 473, 1108 [10]. Hezaveh Y. D.,
Levasseur L. P., Marshall P. J., 2017, Nature, 548, 555.
[11]. Lanusse F., Ma Q., Li N., Collett T. E., Li C.-L., Ravanbakhsh S., Mandelbaum R., Póczos B., 2018, Monthly Notices of the Royal
Astronomical Society, 473, 3895.
[12]. Ntampaka M., Trac H., Sutherland D. J., Battaglia N., Póczos B., Schneider J., 2015, The Astrophysical Journal, 803, 50. [13]. Kim E. J.,
Brunner R. J., 2017, Monthly Notices of the Royal Astronomical Society, 464, 4463.
[14]. Xu X., Ho S., Trac H., Schneider J., Poczos B., Ntampaka M., 2013, The Astrophysical Journal, 772, 147. [15]. Smirnov E. A., Markov A.
B., 2017, Monthly Notices of the Royal Astronomical Society, 469, 2024. [16]. Hoyle B., 2016, Astronomy and Computing, l6, 34.
[17]. D'Isanto A., Polsterer K. L., 2018, A&A, 609, A111.
[18]. Pasquet J., Bertin E., Treyer M., Arnouts S., Fouchez D., 2019, A&A, 621, A26.
[19]. “Sloan Digital Sky Survey | Alfred P. Sloan Foundation.” Sloan Digital Sky Survey, sloan.org/programs/research/sloan-digital-sky-survey.
[20]. York, Donald & Adelman, Jennifer & Anderson, John & Anderson, Scott & Annis, James & Bahcall, N. & Bakken, JA & Barkhouser,
Robert & Bastian, Steven & Berman, Eileen & Boroski, William & Bracker, Steve & Briegel, C. & Briggs, John & Brinkmann, Jon & Brunner,
Robert & Burles, Scott & Carey, Larry & Yasuda, and. (2007). The Sloan Digital Sky Survey: Technical Summary. The Astronomical Journal.
120. 1579. 10.1086/301513.
[21]. Margony, B. (1999). The Sloan Digital Sky Survey. Philosophical Transactions of the Royal Society A: Mathematical, Physical and
Engineering Sciences, 357(1750), 93–103.
[22]. Chai, Tianfeng & Draxler, R.. (2014). Root mean square error (RMSE) or mean absolute error (MAE)?. Geosci. Model Dev.. 7.
10.5194/gmdd-7- 1525-2014.
[23]. Yan, Q.; Yang, B.; Wang, W.; Wang, B.; Chen, P.; Zhang, J. Apple Leaf Diseases Recognition Based on An Improved Convolutional
Neural Network. Sensors 2020, 20, 3535.
[24]. Mandal, M. (n.d.). CNN for Deep Learning | Convolutional Neural Networks. Analytics Vidhya.
https://www.analyticsvidhya.com/blog/2021/05/convolutional-neural-networks-cnn/
[25]. Yamashita, R., Nishio, M., Do, R.K.G. et al. Convolutional neural networks: an overview and application in radiology. Insights Imaging 9,
611–629 (2018).
[26]. Koonce, B. (2021). Resnet 34. In: Convolutional Neural Networks With Swift For Tensorflow. Apress, Berkeley, Ca.
[27]. Anna Gallazzi, Stéphane Charlot, Jarle Brinchmann, Simon D. M. White, Christy A. Tremonti, The Ages And Metallicities Of Galaxies In
The Local Universe, Monthly Notices Of The Royal Astronomical Society, Volume 362, Issue 1, September 2005, Pages 41–58.
[28]. Gao, Mingyu & Chen, Jianfeng & Mu, Hongbo & Qi, Dawei. (2021). A Transfer Residual Neural Network Based on ResNet-34 for
Detection of Wood Knot Defects. Forests. 12. 212. 10.3390/f12020212.
[29].Xie,Saining; Girshick, Ross; Dollar, Piotr; Tu, Zhuowen; He, Kiming (2017),[IEEE 2017 IEEE Conference and Computer vision and
pattern Recognition (CVPR) – Hnolulu, Hi (2017.7.21-2017.7.26)] 2017 IEEE Conference on Computer Vision and pattern Recognition
(CVPR)- Aggregated Residual Transformation for Deep Nerual Networks 5987-5995.
[30]. Park, Ji & Wagner-Carena, Sebastian & Birrer, Simon & Marshall, Philip & Lin, Joshua & Roodman, Aaron. (2020). Large-Scale
Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant.
[31]. Breiman, L. Random Forests. Machine Learning 45, 5–32 (2001).
[32]. Gao, YuLong, Bao, Min, Yuan, QiRong, Kong, Xu, Zou, Hu, Zhou, Xu, Gu, Yizhou, Lin, Zesen, Liang, Zhixiong, and Huang, Chi. Mass–
Metallicity Relation and Fundamental Metallicity Relation of Metal-poor Star-forming Galaxies at 0.6<$Z$<0.9 from the eBOSS Survey.
United States: N. p., 2018.
[33]. Camera | SDSS. (n.d.). SDSS. Retrieved May 27, 2022, from https://www.sdss.org/instruments/camera/
[34]. Simonyan, K. and Zisserman, A., “Very Deep Convolutional Networks for Large-Scale Image Recognition”, 2014. [35]. Smith L. N. et al,
2015, preprint, (arXiv:1506.01186) The Dark Energy Survey Collaboration 2005.
[36]. Loshchilov, Ilya & Hutter, Frank. (2016). SGDR: Stochastic Gradient Descent with Warm Restarts.
[37]. Freedman D., Diaconis P., 1981, Zeitschrift fur Wahrschein- ¨lichkeitstheorie und Verwandte Gebiete, 57, 453. [38]. Tremonti C. A., et al.,
2004, The Astrophysical Journal, 613, 898.
[38]. Tremonti C. A., et al., 2004, The Astrophysical Journal, 613, 898.
[39]. Brinchmann J., Charlot S., White S. D. M., Tremonti C., Kauffmann G., Heckman T., Brinkmann J., 2004, Monthly Notices of the
Royal Astronomical Society, 351, 1151
1.
[2]. Wheeler, J. Craig; Sneden, Christopher (1989). Abundance Ratios as a Function of Metallicity. Annual Review of Astronomy and
Astrophysics, 27(1), 279– 349.
[3]. John F Wu, Steven Boada, Using Convolutional Neural Networks To Predict Galaxy Metallicity From Three-Color Images, Monthly
Notices Of The Royal Astronomical Society, Volume 484, Issue 4, April 2019, Pages 4683–4694.
[4]. Wu, John F.“Deep Learning With Galaxy Images.”GitHub,
jwuphysics.github.io/blog/galaxies/astrophysics/deep%20learning/computer%20vision/2020/05/21/exploring-galaxies-with-deep-learning.html.
[5]. Lacy, M., Riley, J. M., Waldram, E. M., McMahon, R. G., & Warner, P. J. (1995). "A radio-optical survey of the North Ecliptic CAP".
Monthly Notices of the Royal Astronomical Society. 276 (2): 614–626.
[6]. Dieleman S., Willett K. W., Dambre J., 2015, Monthly Notices of the Royal Astronomical Society, 450, 1441. [7]. Huertas-Company M., et
al., 2015, The Astrophysical Journal Supplemnent Series, 221, 8.
[8]. Beck M. R., et al., 2018, Monthly Notices of the Royal Astronomical Society, 476, 5516.[9]. Hocking A., Geach J. E., Sun Y., Davey N., 2018, Monthly Notices of the Royal Astronomical Society, 473, 1108 [10]. Hezaveh Y. D.,
Levasseur L. P., Marshall P. J., 2017, Nature, 548, 555.
[11]. Lanusse F., Ma Q., Li N., Collett T. E., Li C.-L., Ravanbakhsh S., Mandelbaum R., Póczos B., 2018, Monthly Notices of the Royal
Astronomical Society, 473, 3895.
[12]. Ntampaka M., Trac H., Sutherland D. J., Battaglia N., Póczos B., Schneider J., 2015, The Astrophysical Journal, 803, 50. [13]. Kim E. J.,
Brunner R. J., 2017, Monthly Notices of the Royal Astronomical Society, 464, 4463.
[14]. Xu X., Ho S., Trac H., Schneider J., Poczos B., Ntampaka M., 2013, The Astrophysical Journal, 772, 147. [15]. Smirnov E. A., Markov A.
B., 2017, Monthly Notices of the Royal Astronomical Society, 469, 2024. [16]. Hoyle B., 2016, Astronomy and Computing, l6, 34.
[17]. D'Isanto A., Polsterer K. L., 2018, A&A, 609, A111.
[18]. Pasquet J., Bertin E., Treyer M., Arnouts S., Fouchez D., 2019, A&A, 621, A26.
[19]. “Sloan Digital Sky Survey | Alfred P. Sloan Foundation.” Sloan Digital Sky Survey, sloan.org/programs/research/sloan-digital-sky-survey.
[20]. York, Donald & Adelman, Jennifer & Anderson, John & Anderson, Scott & Annis, James & Bahcall, N. & Bakken, JA & Barkhouser,
Robert & Bastian, Steven & Berman, Eileen & Boroski, William & Bracker, Steve & Briegel, C. & Briggs, John & Brinkmann, Jon & Brunner,
Robert & Burles, Scott & Carey, Larry & Yasuda, and. (2007). The Sloan Digital Sky Survey: Technical Summary. The Astronomical Journal.
120. 1579. 10.1086/301513.
[21]. Margony, B. (1999). The Sloan Digital Sky Survey. Philosophical Transactions of the Royal Society A: Mathematical, Physical and
Engineering Sciences, 357(1750), 93–103.
[22]. Chai, Tianfeng & Draxler, R.. (2014). Root mean square error (RMSE) or mean absolute error (MAE)?. Geosci. Model Dev.. 7.
10.5194/gmdd-7- 1525-2014.
[23]. Yan, Q.; Yang, B.; Wang, W.; Wang, B.; Chen, P.; Zhang, J. Apple Leaf Diseases Recognition Based on An Improved Convolutional
Neural Network. Sensors 2020, 20, 3535.
[24]. Mandal, M. (n.d.). CNN for Deep Learning | Convolutional Neural Networks. Analytics Vidhya.
https://www.analyticsvidhya.com/blog/2021/05/convolutional-neural-networks-cnn/
[25]. Yamashita, R., Nishio, M., Do, R.K.G. et al. Convolutional neural networks: an overview and application in radiology. Insights Imaging 9,
611–629 (2018).
[26]. Koonce, B. (2021). Resnet 34. In: Convolutional Neural Networks With Swift For Tensorflow. Apress, Berkeley, Ca.
[27]. Anna Gallazzi, Stéphane Charlot, Jarle Brinchmann, Simon D. M. White, Christy A. Tremonti, The Ages And Metallicities Of Galaxies In
The Local Universe, Monthly Notices Of The Royal Astronomical Society, Volume 362, Issue 1, September 2005, Pages 41–58.
[28]. Gao, Mingyu & Chen, Jianfeng & Mu, Hongbo & Qi, Dawei. (2021). A Transfer Residual Neural Network Based on ResNet-34 for
Detection of Wood Knot Defects. Forests. 12. 212. 10.3390/f12020212.
[29].Xie,Saining; Girshick, Ross; Dollar, Piotr; Tu, Zhuowen; He, Kiming (2017),[IEEE 2017 IEEE Conference and Computer vision and
pattern Recognition (CVPR) – Hnolulu, Hi (2017.7.21-2017.7.26)] 2017 IEEE Conference on Computer Vision and pattern Recognition
(CVPR)- Aggregated Residual Transformation for Deep Nerual Networks 5987-5995.
[30]. Park, Ji & Wagner-Carena, Sebastian & Birrer, Simon & Marshall, Philip & Lin, Joshua & Roodman, Aaron. (2020). Large-Scale
Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant.
[31]. Breiman, L. Random Forests. Machine Learning 45, 5–32 (2001).
[32]. Gao, YuLong, Bao, Min, Yuan, QiRong, Kong, Xu, Zou, Hu, Zhou, Xu, Gu, Yizhou, Lin, Zesen, Liang, Zhixiong, and Huang, Chi. Mass–
Metallicity Relation and Fundamental Metallicity Relation of Metal-poor Star-forming Galaxies at 0.6<$Z$<0.9 from the eBOSS Survey.
United States: N. p., 2018.
[33]. Camera | SDSS. (n.d.). SDSS. Retrieved May 27, 2022, from https://www.sdss.org/instruments/camera/
[34]. Simonyan, K. and Zisserman, A., “Very Deep Convolutional Networks for Large-Scale Image Recognition”, 2014. [35]. Smith L. N. et al,
2015, preprint, (arXiv:1506.01186) The Dark Energy Survey Collaboration 2005.
[36]. Loshchilov, Ilya & Hutter, Frank. (2016). SGDR: Stochastic Gradient Descent with Warm Restarts.
[37]. Freedman D., Diaconis P., 1981, Zeitschrift fur Wahrschein- ¨lichkeitstheorie und Verwandte Gebiete, 57, 453. [38]. Tremonti C. A., et al.,
2004, The Astrophysical Journal, 613, 898.
[38]. Tremonti C. A., et al., 2004, The Astrophysical Journal, 613, 898.
[39]. Brinchmann J., Charlot S., White S. D. M., Tremonti C., Kauffmann G., Heckman T., Brinkmann J., 2004, Monthly Notices of the
Royal Astronomical Society, 351, 1151
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