1 |
J. He, et al., Rapid radionuclide identification algorithm based on the discrete cosine transform and BP neural network, Ann. Nucl. Energy 112 (2018) 1-8.
DOI
|
2 |
M.K. Sharma, A.B. Alajo, H.K. Lee, Three-dimensional localization of low activity gamma-ray sources in real-time scenarios, Nucl. Instrum. Meth. A 813 (2016) 132-138.
DOI
|
3 |
R. Vilim, R. Klann, Radtrac: a system for detecting, localizing, and tracking radioactive sources in real time, Nucl. Technol. 168 (2009) 61-73.
DOI
|
4 |
N.S. Rao, et al., Identification of low-level point radiation sources using a sensor network, in: Proceedings of the 7th International Conference on Information Processing in Sensor Networks, IEEE Computer Society, 2008.
|
5 |
R.J. Nemzek, et al., Distributed sensor networks for detection of mobile radioactive sources, IEEE Trans. Nucl. Sci. 51 (2004) 1693-1700.
DOI
|
6 |
H.E. Baidoo-Williams, et al., On the gradient descent localization of radioactive sources, IEEE Signal Process. Lett. 20 (2013) 1046-1049.
DOI
|
7 |
F. Chollet, Deep Learning mit Python und Keras: Das Praxis-Handbuch vom Entwickler der Keras-Bibliothek, MITP-Verlags GmbH & Co. KG, 2018.
|
8 |
A. Kumar, et al., Automated sequential search for weak radiation sources, in: 2006 14th Mediterranean Conference on Control and Automation, IEEE, 2006.
|
9 |
P. Kump, et al., Detection of shielded radionuclides from weak and poorly resolved spectra using group positive RIVAL, Radiat. Meas. 48 (2013) 18-28.
DOI
|
10 |
M. Chandy, C. Pilotto, R. McLean, Networked sensing systems for detecting people carrying radioactive material, in: 2008 5th International Conference on Networked Sensing Systems, IEEE, 2008.
|
11 |
J.-P. He, et al., Spectrometry analysis based on approximation coefficients and deep belief networks, Nucl. Sci. Tech. 29 (2018) 69.
DOI
|
12 |
E.-w. Bai, et al., Maximum likelihood localization of radioactive sources against a highly fluctuating background, IEEE Trans. Nucl. Sci. 62 (2015) 3274-3282.
DOI
|
13 |
M.R. Morelande, B. Ristic, Radiological source detection and localisation using Bayesian techniques, IEEE Trans. Signal Process. 57 (2009) 4220-4231.
DOI
|
14 |
R.A. Cortez, et al., Smart radiation sensor management, IEEE Robot. Autom. Mag. 15 (2008) 85-93.
DOI
|
15 |
Z. Liu, S. Abbaszadeh, Double Q-learning for radiation source detection, Sensors 19 (2019) 960.
DOI
|
16 |
P. Olmos, et al., Application of neural network techniques in gamma spectroscopy, Nucl. Instrum. Meth. A 312 (1992) 167-173.
DOI
|
17 |
J. Allison, et al., Geant4 developments and applications. Communications of the ACMIEEE trans, Signal Process IEEE Trans. Nucl. Sci. 53 (2006) 270-278.
DOI
|
18 |
J. Wu, Introduction to Convolutional Neural Networks, vol. 5, National Key Lab for Novel Software Technology. Nanjing University, China, 2017, p. 23.
|
19 |
Y. LeCun, Y. Bengio, G. Hinton, Deep learning, Nature 521 (2015) 436-444.
DOI
|
20 |
A. Gunatilaka, B. Ristic, R. Gailis, On localisation of a radiological point source, in: 2007 Information, Decision and Control, IEEE, 2007.
|
21 |
I. Vasilev, Python Deep Learning: Exploring Deep Learning Techniques and Neural Network Architectures with PyTorch, Keras, and TensorFlow, 2019.
|
22 |
M. Hutchinson, H. Oh, W.-H. Chen, Adaptive Bayesian sensor motion planning for hazardous source term reconstruction, IFAC-PapersOnLine 50 (2017) 2812-2817.
DOI
|
23 |
B. Deb, Iterative estimation of location and trajectory of radioactive sources with a networked system of detectors, IEEE Trans. Nucl. Sci. 60 (2013) 1315-1326.
DOI
|
24 |
A.H. Liu, J.J. Bunn, K.M. Chandy, Sensor networks for the detection and tracking of radiation and other threats in cities, in: Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks, IEEE, 2011.
|
25 |
M. Morelande, B. Ristic, A. Gunatilaka, Detection and parameter estimation of multiple radioactive sources, in: 2007 10th International Conference on Information Fusion, IEEE, 2007.
|
26 |
J.-I. Byun, H.-Y. Choi, J.-Y. Yun, A 4-point in-situ method to locate a discrete gamma-ray source in 3-D space, Appl. Radiat. Isot. 68 (2010) 370-377.
DOI
|
27 |
A.F. Alwars, F. Rahmani, Conceptual design of an orphan gamma source finder, Nucl. Instrum Meth. A 922 (2019) 235-242.
DOI
|
28 |
T. Liu, et al., Implementation of Training Convolutional Neural Networks, 2015 arXiv preprint arXiv:1506.01195.
|
29 |
B. Ristic, M. Morelande, A. Gunatilaka, Information driven search for point sources of gamma radiation, Signal Process. 90 (2010) 1225-1239.
DOI
|
30 |
C.G. Mayhew, R.G. Sanfelice, A.R. Teel, Robust source-seeking hybrid controllers for autonomous vehicles, in: 2007 American Control Conference, IEEE, 2007.
|
31 |
A. Gulli, S. Pal, Deep Learning with Keras, Packt Publishing Ltd, 2017.
|
32 |
R. Atienza, Advanced Deep Learning with Keras: Apply Deep Learning Techniques, Autoencoders, GANs, Variational Autoencoders, Deep Reinforcement Learning, Policy Gradients, and More, Packt Publishing Ltd, 2018.
|