• Photonics Research
  • Vol. 9, Issue 4, B109 (2021)
Linh V. Nguyen1、*, Cuong C. Nguyen2, Gustavo Carneiro2, Heike Ebendorff-Heidepriem1、3, and Stephen C. Warren-Smith1、3、4
Author Affiliations
  • 1Institute for Photonics and Advanced Sensing and School of Physical Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
  • 2Australian Institute for Machine Learning, The University of Adelaide, Adelaide, SA 5005, Australia
  • 3Australian Research Council Centre of Excellence for Nanoscale BioPhotonics, The University of Adelaide, SA 5005, Australia
  • 4Future Industries Institute, University of South Australia, Mawson Lakes, SA 5095, Australia
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    DOI: 10.1364/PRJ.415902 Cite this Article Set citation alerts
    Linh V. Nguyen, Cuong C. Nguyen, Gustavo Carneiro, Heike Ebendorff-Heidepriem, Stephen C. Warren-Smith. Sensing in the presence of strong noise by deep learning of dynamic multimode fiber interference[J]. Photonics Research, 2021, 9(4): B109 Copy Citation Text show less
    References

    [1] D. A. Krohn, T. W. MacDougall, A. Mendez. Fiber Optic Sensors: Fundamentals and Applications(2015).

    [2] B. Lee. Review of the present status of optical fiber sensors. Opt. Fibre Technol., 9, 57-79(2003).

    [3] X. Wang, O. S. Wolfbeis. Fiber-optic chemical sensors and biosensors (2015–2019). Anal. Chem., 92, 397-430(2020).

    [4] X. He, C. Ma, S. Wang, Z. Wang, L. Yuan. Pressure vector sensor based on an orthogonal optical path Sagnac interferometer. Opt. Express, 28, 7969-7979(2020).

    [5] Q. Tian, G. Xin, K.-S. Lim, Y. He, J. Liu, H. Ahmad, X. Liu, H. Yang. Cascaded Fabry-Perot interferometer-regenerated fiber Bragg grating structure for temperature-strain measurement under extreme temperature conditions. Opt. Express, 28, 30478-30488(2020).

    [6] V. Bhatia, D. Campbell, R. O. Claus, A. M. Vengsarkar. Simultaneous strain and temperature measurement with long-period gratings. Opt. Lett., 22, 648-650(1997).

    [7] X. Li, L. V. Nguyen, H. Ebendorff-Heidepriem, D. Pham, S. C. Warren-Smith. Simultaneous measurement of temperature and refractive index using an exposed core micro structured optical fiber. IEEE J. Sel. Quantum Electron., 26, 5600107(2020).

    [8] 8Google Scholar search using “simultaneous measurement fiber sensor,” accessed October 25, 2020.

    [9] B. Rahmani, D. Loterie, G. Konstantinou, D. Psaltis, C. Moser. Multimode optical fiber transmission with a deep learning network. Light Sci. Appl., 7, 69(2018).

    [10] T. D. Cabral, E. Fujiwara, S. C. Warren-Smith, H. Ebendorff-Heidepriem, C. M. B. Cordeiro. Multimode exposed core fiber specklegram sensor. Opt. Lett., 45, 3212-3215(2020).

    [11] A. Yariv. Phase conjugate optics and real-time holography. IEEE J. Quantum Electron., 14, 650-660(1978).

    [12] I. N. Papadopoulos, S. Farahi, C. Moser, D. Psaltis. Focusing and scanning light through a multimode optical fiber using digital phase conjugation. Opt. Express, 20, 10583-10590(2012).

    [13] T. Čižmár, K. Dholakia. Shaping the light transmission through a multimode optical fibre: complex transformation analysis and applications in biophotonics. Opt. Express, 19, 18871-18884(2011).

    [14] S. Bianchi, R. Di Leonardo. A multi-mode fiber probe for holographic micromanipulation and microscopy. Lab Chip, 12, 635-639(2012).

    [15] Y. Choi, C. Yoon, M. Kim, T. D. Yang, C. Fang-Yen, R. R. Dasari, K. J. Lee, W. Choi. Scanner-free and wide-field endoscopic imaging by using a single multimode optical fiber. Phys. Rev. Lett., 109, 203901(2012).

    [16] A. M. Caravaca-Aguirre, E. Niv, D. B. Conkey, R. Piestun. Real-time resilient focusing through a bending multimode fiber. Opt. Express, 21, 12881-12887(2013).

    [17] M. N’Gom, T. B. Norris, E. Michielssen, R. R. Nadakuditi. Mode control in a multimode fiber through acquiring its transmission matrix from a reference-less optical system. Opt. Lett., 43, 419-422(2018).

    [18] N. Borhani, E. Kakkava, C. Moser, D. Psaltis. Learning to see through multimode fibers. Optica, 5, 960-966(2018).

    [19] R. K. Gupta, R. D. Bruce, S. J. Powis, K. Dholakia. Deep learning enabled laser speckle wavemeter with a high dynamic range. Laser Photon. Rev., 14, 2000120(2020).

    [20] W. Xiong, B. Redding, S. Gertler, Y. Bromberg, H. D. Tagare, H. Cao. Deep learning of ultrafast pulses with a multimode fiber. APL Photon., 5, 096106(2020).

    [21] J. Wang, B. Dong, E. Lally, J. Gong, M. Han, A. Wang. Multiplexed high temperature sensing with sapphire fiber air gap-based extrinsic Fabry–Perot interferometers. Opt. Lett., 35, 619-621(2010).

    [22] T. Habisreuther, T. Elsmann, Z. Pan, A. Graf, R. Willsch, M. A. Schmidt. Sapphire fiber Bragg gratings for high temperature and dynamic temperature diagnostics. Appl. Therm. Eng., 91, 860-865(2015).

    [23] D. Grobnic, S. J. Mihailov, C. W. Smelser, H. Ding. Sapphire fiber Bragg grating sensor made using femtosecond laser radiation for ultrahigh temperature applications. IEEE Photon. Technol. Lett., 16, 2505-2507(2004).

    [24] X. Zhu, A. Schülzgen, H. Li, L. Li, L. Han, J. V. Moloney, N. Peyghambarian. Detailed investigation of self-imaging in large core multimode optical fibers for application in fiber lasers and amplifiers. Opt. Express, 16, 16632-16645(2008).

    [25] Y. LeCun, Y. Bengio, G. Hinton. Deep learning. Nature, 521, 436-444(2015).

    [26] T. Wieduwilt, J. Dellith, F. Talkenberg, H. Bartelt, M. A. Schmidt. Reflectivity enhanced refractive index sensor based on a fiber-integrated Fabry-Perot microresonator. Opt. Express, 22, 25333-25346(2014).

    [27] S. C. Warren-Smith, R. Kostecki, L. V. Nguyen, T. M. Monro. Fabrication, splicing, Bragg grating writing, and polyelectrolyte functionalization of exposed-core microstructured optical fibers. Opt. Express, 22, 29493-29504(2014).

    [28] L. V. Nguyen, K. Hill, S. C. Warren-Smith, T. M. Monro. Interferometric-type optical biosensor based on exposed-core microstructured optical fiber. Sens. Actuators B, 221, 320-327(2015).

    [29] S. Pevec, D. Donlagic. High resolution, all-fiber, micro-machined sensor for simultaneous measurement of refractive index and temperature. Opt. Express, 22, 16241-16253(2014).

    [30] J. W. Silverstone, S. McFarlane, C. P. K. Manchee, A. Meldrum. Ultimate resolution for refractometric sensing with whispering gallery mode microcavities. Opt. Express, 20, 8284-8295(2012).

    [31] Y. Jiang. Fourier transform white-light interferometry for the measurement of fiber-optic extrinsic Fabry-Pérot interferometric sensors. IEEE Photon. Tech. Lett., 20, 75-77(2008).

    [32] Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbart, L. D. Jackel. Backpropagation applied to handwritten zip code recognition. Neural Comput., 1, 541-551(1989).

    [33] S. Aisawa, K. Noguchi, T. Matsumoto. Remote image classification through multimode optical fiber using a neural network. Opt. Lett., 16, 645-647(1991).

    [34] T. Matsumoto, M. Koga, K. Noguchi, S. Aizawa. Proposal for neural-network applications to fiber-optic transmission. Proceedings of 1990 IJCNN International Joint Conference on Neural Networks, 75-80(1990).

    [35] R. K. Marusarz, M. R. Sayeh. Neural network-based multimode fiber-optic information transmission. Appl. Opt., 40, 219-227(2001).

    [36] P. Caramazza, O. Moran, R. Murray-Smith, D. Faccio. Transmission of natural scene images through a multimode fibre. Nat. Commun., 10, 2029(2019).

    [37] T. Hastie, R. Tibshirani, J. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Prediction(2009).

    [38] R. H. R. Hahnloser, R. Sarpeshkar, M. A. Mahowald, R. J. Douglas, H. S. Seung. Digital selection and analogue amplification coexist in a cortex-inspired silicon circuit. Nature, 405, 947-951(2000).

    [39] D. K. Diederik, J. L. Ba. Adam: a method for stochastic optimization(2014).

    [40] https://keras.io/. https://keras.io/

    [41] http://www.image-net.org/. http://www.image-net.org/

    [42] B. Redding, S. M. Popoff, H. Cao. All-fiber spectrometer based on speckle pattern reconstruction. Opt. Express, 21, 6584-6600(2013).

    [43] J. Quionero-Candela, M. Sugiyama, A. Schwaighofer, N. Lawrence. Dataset Shift in Machine Learning(2009).

    [44] R. Alaiz-Rodríguez, N. Japkowicz. Assessing the impact of changing environments on classifier performance. Advances in Artificial Intelligence, 13-24(2008).

    [45] M. Wang, W. Deng. Deep visual domain adaptation: a survey. Neurocomputing, 312, 135-153(2018).

    [46] D. Tasche. Fisher consistency for prior probability shift. J. Mach. Learn. Res., 18, 1-32(2017).

    [47] S. Geman, E. Bienenstock, R. Doursat. Neural networks and the bias/variance dilemma. Neural Comput., 4, 1-58(1992).

    [48] O. Bousquet, A. Elisseeff. Stability and generalization. J. Mach. Learn. Res., 2, 499-526(2002).

    [49] C. Zhang, S. Bengio, M. Hardt, B. Recht, O. Vinyals. Understanding deep learning requires rethinking generalization. International Conference on Learning Representation, 1-15(2017).

    [50] A. Ng. Machine learning yearning: technical strategy for AI engineers in the era of deep learning.

    [51] I. Goodfellow, Y. Bengio, A. Courville. Deep Learning(2016).

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    Linh V. Nguyen, Cuong C. Nguyen, Gustavo Carneiro, Heike Ebendorff-Heidepriem, Stephen C. Warren-Smith. Sensing in the presence of strong noise by deep learning of dynamic multimode fiber interference[J]. Photonics Research, 2021, 9(4): B109
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