164
N. S. Philip
In all the models described in this article, features had to be extracted and supplied
to the model for training. This gives a lot of control on the training process by allowing to filter out unwanted information. However, it also makes it difficult to model
complex systems. Modern machine learning tools that the author currently work on
uses methods such as Convolution Neural Networks(CNN), semantic segmentation
and LSTM for automating feature detection and classification from row images.
References
1. S.A. Gelman, Annu. Rev. Psychol. 60, 115 (2009)
2. S. Linnainmaa, Master’s thesis, Linnainmaa (1970)
3. B.J. Wythoff, Chemom. Intell. Lab. Sys.18(2), 115 (1993)
4. B.J. Ninan, Neurocomputing 47(1), 21 (2002)
5. B.J. Ninan, Comput. Geosci. 29(2), 215 (2003)
6. B.J. Ninan, et al., Intell. Data Anal. 4, 463 (2000)
7. K. Ninan, Astrono. Astrophys. 385(3), 1119 (2002)
8. N. Sheelu, et al., Mon. Not. R. Astron. Soc.419, 80 (2012)
9. S. Nikhil, et al., Phys. Rev. D.95, 104059 (2017)
10. http://rasbt.github.io/mlxtend/userguide/generalconcepts/gradient-optimization
11. Simeon Kostadinov, Mirror, 8 Aug 2019
12. https://patrickhoo.wixsite.com/diveindatascience/singlepost/2019/06/13/Activationfunctions-and-when-to-use-them
13. https://www.ligo.caltech.edu/image/ligo20150731e
N. S. Philip
In all the models described in this article, features had to be extracted and supplied
to the model for training. This gives a lot of control on the training process by allowing to filter out unwanted information. However, it also makes it difficult to model
complex systems. Modern machine learning tools that the author currently work on
uses methods such as Convolution Neural Networks(CNN), semantic segmentation
and LSTM for automating feature detection and classification from row images.
References
1. S.A. Gelman, Annu. Rev. Psychol. 60, 115 (2009)
2. S. Linnainmaa, Master’s thesis, Linnainmaa (1970)
3. B.J. Wythoff, Chemom. Intell. Lab. Sys.18(2), 115 (1993)
4. B.J. Ninan, Neurocomputing 47(1), 21 (2002)
5. B.J. Ninan, Comput. Geosci. 29(2), 215 (2003)
6. B.J. Ninan, et al., Intell. Data Anal. 4, 463 (2000)
7. K. Ninan, Astrono. Astrophys. 385(3), 1119 (2002)
8. N. Sheelu, et al., Mon. Not. R. Astron. Soc.419, 80 (2012)
9. S. Nikhil, et al., Phys. Rev. D.95, 104059 (2017)
10. http://rasbt.github.io/mlxtend/userguide/generalconcepts/gradient-optimization
11. Simeon Kostadinov, Mirror, 8 Aug 2019
12. https://patrickhoo.wixsite.com/diveindatascience/singlepost/2019/06/13/Activationfunctions-and-when-to-use-them
13. https://www.ligo.caltech.edu/image/ligo20150731e