-
1
-
-
54249143198
-
Microwave and Millimeter Wave Sensors for Crack Detection
-
Zoughi, R.; Kharkovsky, S. Microwave and Millimeter Wave Sensors for Crack Detection. Fatigue Fract. Eng. Mater. Struct. 2008, 31, 695–713.
-
(2008)
Fatigue Fract. Eng. Mater. Struct
, vol.31
, pp. 695-713
-
-
Zoughi, R.1
Kharkovsky, S.2
-
2
-
-
84881335664
-
Metal defects sizing and detection under thick coating using microwave
-
Zhang, H.; Gao, B.; Tian, G.Y.; Woo, W.L.; Bai, L. Metal defects sizing and detection under thick coating using microwave. NDT&E Int. 2013, 60, 52–61.
-
(2013)
Ndt&E Int
, vol.60
, pp. 52-61
-
-
Zhang, H.1
Gao, B.2
Tian, G.Y.3
Woo, W.L.4
Bai, L.5
-
3
-
-
77952268120
-
Depth evaluation of shallow surface cracks in metals using rectangular waveguides at millimeter-wave frequencies
-
McClanahan, A.; Kharkovsky, S.; Maxon, A.R.; Zoughi, R.; Palmer, D.D. Depth evaluation of shallow surface cracks in metals using rectangular waveguides at millimeter-wave frequencies. IEEE Trans. Instrum. Meas. 2010, 59, 1693–1704.
-
(2010)
IEEE Trans. Instrum. Meas
, vol.59
, pp. 1693-1704
-
-
McClanahan, A.1
Kharkovsky, S.2
Maxon, A.R.3
Zoughi, R.4
Palmer, D.D.5
-
6
-
-
84898467464
-
Waveguide Probe Loaded With Split-Ring Resonators for Crack Detection in Metallic Surfaces
-
Hu, B.; Ren, Z.; Boybay, M.; Ramahi, O. Waveguide Probe Loaded With Split-Ring Resonators for Crack Detection in Metallic Surfaces. IEEE Trans. Microw. Theory Tech. 2014, 62, 871–878.
-
(2014)
IEEE Trans. Microw. Theory Tech
, vol.62
, pp. 871-878
-
-
Hu, B.1
Ren, Z.2
Boybay, M.3
Ramahi, O.4
-
7
-
-
33846956777
-
The application of machine learning to structural health monitoring
-
Worden, K.; Manson, G. The application of machine learning to structural health monitoring. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2007, 365, 515–537.
-
(2007)
Philos. Trans. R. Soc. A Math. Phys. Eng. Sci
, vol.365
, pp. 515-537
-
-
Worden, K.1
Manson, G.2
-
8
-
-
80053159949
-
Breast cancer detection based on differential ultrawideband microwave radar
-
Byrne, D.; O’Halloran, M.; Glavin, M.; Jones, E. Breast cancer detection based on differential ultrawideband microwave radar. Prog. Electromagn. Res. M 2011, 20, 231–242.
-
(2011)
Prog. Electromagn. Res. M
, vol.20
, pp. 231-242
-
-
Byrne, D.1
O’Halloran, M.2
Glavin, M.3
Jones, E.4
-
9
-
-
80053137377
-
Support vector machine-based ultrawideband breast cancer detection system
-
Byrne, D.; O’Halloran, M.; Jones, E.; Glavin, M. Support vector machine-based ultrawideband breast cancer detection system. J. Electromagn. Waves Appl. 2011, 25, 1807–1816.
-
(2011)
J. Electromagn. Waves Appl
, vol.25
, pp. 1807-1816
-
-
Byrne, D.1
O’Halloran, M.2
Jones, E.3
Glavin, M.4
-
10
-
-
78650506365
-
UWB Imaging for Breastr Cancer Detection Using Neural Network
-
AlShehri, S.A.; Khatun, S. UWB Imaging for Breastr Cancer Detection Using Neural Network. Prog. Electromagn. Res. C 2009, 7, 79–93.
-
(2009)
Prog. Electromagn. Res. C
, vol.7
, pp. 79-93
-
-
Alshehri, S.A.1
Khatun, S.2
-
11
-
-
80051960151
-
Measurement of complex permittivity using artificial neural networks
-
Hasan, A.; Peterson, A.F. Measurement of complex permittivity using artificial neural networks. IEEE Antennas Propag. Mag. 2011, 53, 200–203.
-
(2011)
IEEE Antennas Propag. Mag
, vol.53
, pp. 200-203
-
-
Hasan, A.1
Peterson, A.F.2
-
12
-
-
0003922190
-
-
John Wiley & Sons: New York, NY, USA
-
Duda, R.O.; Hart, P.E.; Stork, D.G. Pattern Classification; John Wiley & Sons: New York, NY, USA, 1999.
-
(1999)
Pattern Classification
-
-
Duda, R.O.1
Hart, P.E.2
Stork, D.G.3
-
13
-
-
54249143198
-
Microwave and millimetre wave sensors for crack detection
-
Zoughi, R.; Kharkovsky, S. Microwave and millimetre wave sensors for crack detection. Fatigue Fract. Eng. Mater. Struct. 2008, 31, 695–713.
-
(2008)
Fatigue Fract. Eng. Mater. Struct
, vol.31
, pp. 695-713
-
-
Zoughi, R.1
Kharkovsky, S.2
-
14
-
-
69449085714
-
Machine learning: A crucial tool for sensor design
-
Zhao, W.; Bhushan, A.; Santamaria, A.D.; Simon, M.G.; Davis, C.E. Machine learning: A crucial tool for sensor design. Algorithms 2008, 1, 130–152.
-
(2008)
Algorithms
, vol.1
, pp. 130-152
-
-
Zhao, W.1
Bhushan, A.2
Santamaria, A.D.3
Simon, M.G.4
Davis, C.E.5
-
15
-
-
0043126911
-
Logistic regression and artificial neural network classification models: A methodology review
-
Dreiseitl, S.; Ohno-Machado, L. Logistic regression and artificial neural network classification models: A methodology review. J. Biomed. Inform. 2002, 35, 352–359.
-
(2002)
J. Biomed. Inform
, vol.35
, pp. 352-359
-
-
Dreiseitl, S.1
Ohno-Machado, L.2
-
16
-
-
0035871395
-
Comparison of artificial neural networks with other statistical approaches
-
Sargent, D.J. Comparison of artificial neural networks with other statistical approaches. Cancer 2001, 91, 1636–1642.
-
(2001)
Cancer
, vol.91
, pp. 1636-1642
-
-
Sargent, D.J.1
-
17
-
-
27144491558
-
Compact size highly directive antennas based on the SRR metamaterial medium
-
Bulu, I.; Caglayan, H.; Aydin, K.; Ozbay, E. Compact size highly directive antennas based on the SRR metamaterial medium. New J. Phys. 2005, 7, doi:10.1088/1367-2630/7/1/223.
-
(2005)
New J. Phys
, pp. 7
-
-
Bulu, I.1
Caglayan, H.2
Aydin, K.3
Ozbay, E.4
-
18
-
-
84929341132
-
The role of geometry of inclusions in forming metamaterials with negative permittivity and permeability
-
Maastricht, The Netherlands, 17–27
-
Engheta, N.; Nelatury, S.R.; Hoorfar, A. The role of geometry of inclusions in forming metamaterials with negative permittivity and permeability. In Proceedings of the 2002 URSI General Assembly, Maastricht, The Netherlands, 17–27 August 2002.
-
(2002)
Proceedings of the 2002 URSI General Assembly
-
-
Engheta, N.1
Nelatury, S.R.2
Hoorfar, A.3
-
19
-
-
84925854653
-
Study of a new metamaterial particle of ‘AV’shape
-
Surat, India, 26–27 December
-
Inamdar, K.; Kosta, Y.; Patnaik, S. Study of a new metamaterial particle of ‘AV’shape. In Proceedings of the 2014 2nd International Conference on Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN), Surat, India, 26–27 December 2014; pp. 1–4.
-
(2014)
Proceedings of the 2014 2Nd International Conference on Emerging Technology Trends in Electronics, Communication and Networking (ET2ECN)
, pp. 1-4
-
-
Inamdar, K.1
Kosta, Y.2
Patnaik, S.3
-
20
-
-
79956293052
-
Asymmetric chiral metamaterial circular polarizer based on four U-shaped split ring resonators
-
Mutlu, M.; Akosman, A.E.; Serebryannikov, A.E.; Ozbay, E. Asymmetric chiral metamaterial circular polarizer based on four U-shaped split ring resonators. Opt. Lett. 2011, 36, 1653–1655.
-
(2011)
Opt. Lett
, vol.36
, pp. 1653-1655
-
-
Mutlu, M.1
Akosman, A.E.2
Serebryannikov, A.E.3
Ozbay, E.4
-
21
-
-
84976252065
-
-
Available online, accessed on 15 May
-
Delac, K.; Grgic, M.; Grgic, S. A Comparative Study of PCA, ICA, and LDA. Available online: http://www.vcl.fer.hr/papers_pdf/A%20Comparative%20Study%20of%20PCA,%20ICA%20and%20LDA.pdf (accessed on 15 May 2015).
-
(2015)
A Comparative Study of PCA, ICA, and LDA
-
-
Delac, K.1
Grgic, M.2
Grgic, S.3
-
22
-
-
84929341134
-
-
Available online, accessed on 15 May
-
Tibaduiza Burgos, D.A.; Mujica Delgado, L.E.; Anaya, M.; Rodellar Benedé, J.; Güemes Gordo, A. Principal Component Analysis vs. Independent Component Analysis for Damage Detection. Available online: http://www.ndt.net/article/ewshm2012/papers/fr1d4.pdf (accessed on 15 May 2015).
-
(2015)
Principal Component Analysis Vs. Independent Component Analysis for Damage Detection
-
-
Tibaduiza Burgos, D.A.1
Mujica Delgado, L.E.2
Anaya, M.3
Rodellar Benedé, J.4
Güemes Gordo, A.5
-
24
-
-
0242415915
-
The comparison of activation functions for multispectral Landsat TM image classification
-
Özkan, C.; Erbek, F.S. The comparison of activation functions for multispectral Landsat TM image classification. Photogramm. Eng. Remote Sens. 2003, 69, 1225–1234.
-
(2003)
Photogramm. Eng. Remote Sens
, vol.69
, pp. 1225-1234
-
-
Özkan, C.1
Erbek, F.S.2
-
25
-
-
84901924319
-
Privacy Preserving Back-Propagation Neural Network Learning Made Practical with Cloud Computing
-
Yuan, J.; Yu, S. Privacy Preserving Back-Propagation Neural Network Learning Made Practical with Cloud Computing. IEEE Trans. Parallel Distrib. Syst. 2014, 25, 212–221.
-
(2014)
IEEE Trans. Parallel Distrib. Syst
, vol.25
, pp. 212-221
-
-
Yuan, J.1
Yu, S.2
-
26
-
-
84868367414
-
Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon
-
Taormina, R.; Chau, K.W.; Sethi, R. Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon. Eng. Appl. Artif. Intell. 2012, 25, 1670–1676.
-
(2012)
Eng. Appl. Artif. Intell
, vol.25
, pp. 1670-1676
-
-
Taormina, R.1
Chau, K.W.2
Sethi, R.3
-
27
-
-
34147105043
-
Application of a PSO-based neural network in analysis of outcomes of construction claims
-
Chau, K. Application of a PSO-based neural network in analysis of outcomes of construction claims. Autom. Constr. 2007, 16, 642–646.
-
(2007)
Autom. Constr
, vol.16
, pp. 642-646
-
-
Chau, K.1
-
28
-
-
33847379879
-
Hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training
-
Zhang, J.R.; Zhang, J.; Lok, T.M.; Lyu, M.R. A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training. Appl. Math. Comput. 2007, 185, 1026–1037.
-
(2007)
Appl. Math. Comput
, vol.185
, pp. 1026-1037
-
-
Zhang, J.R.1
Zhang, J.2
Lok, T.M.3
Lyu, M.4
-
29
-
-
33846516584
-
-
Springer: New York, NY, USA
-
Bishop, C.M.; Jordan, M.; Kleinberg, J.; Scholkopf, B. Pattern Recognition and Machine Learning; Springer: New York, NY, USA, 2006; Volume 1.
-
(2006)
Pattern Recognition and Machine Learning
, vol.1
-
-
Bishop, C.M.1
Jordan, M.2
Kleinberg, J.3
Scholkopf, B.4
-
30
-
-
79955702502
-
LIBSVM: A Library for Support Vector Machines
-
Chang, C.C.; Lin, C.J. LIBSVM: A Library for Support Vector Machines. ACM Trans. Intell. Syst. Technol. 2011, 2, doi:10.1145/1961189.1961199.
-
(2011)
ACM Trans. Intell. Syst. Technol
, pp. 2
-
-
Chang, C.C.1
Lin, C.J.2
-
31
-
-
1942484786
-
Tackling the Poor Assumptions of Naive Bayes Text Classifiers
-
Washington, DC, USA, 21–24
-
Rennie, J.D.M.; Shih, L.; Teevan, J.; Karger, D.R. Tackling the Poor Assumptions of Naive Bayes Text Classifiers. In Proceedings of the Twentieth International Conference on Machine Learning, Washington, DC, USA, 21–24 August 2003; pp. 616–623.
-
(2003)
Proceedings of the Twentieth International Conference on Machine Learning
, pp. 616-623
-
-
Rennie, J.1
Shih, L.2
Teevan, J.3
Karger, D.R.4
-
32
-
-
84875872773
-
Baselines and bigrams: Simple, good sentiment and topic classification
-
Jeju, Korea, 8–14, Short Papers
-
Wang, S.; Manning, C.D. Baselines and bigrams: Simple, good sentiment and topic classification. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Jeju, Korea, 8–14 July 2012; Short Papers-Volume 2, pp. 90–94.
-
(2012)
Proceedings of the 50Th Annual Meeting of the Association for Computational Linguistics
, vol.2
, pp. 90-94
-
-
Wang, S.1
Manning, C.D.2
|