• Acta Photonica Sinica
  • Vol. 49, Issue 4, 0410006 (2020)
Jia-cheng HU1, Di-xin YAN1, Yu-shu SHI2, Lu HUANG2, and Dong-sheng LI1
Author Affiliations
  • 1College of Metrology&Measurement Engineering, University of China Jiliang, Hangzhou 310018, China
  • 2Division of Nano Metrology and Materials Measurement, National Institute of Metrology, Beijing 100029, China
  • show less
    DOI: 10.3788/gzxb20204904.0410006 Cite this Article
    Jia-cheng HU, Di-xin YAN, Yu-shu SHI, Lu HUANG, Dong-sheng LI. Restoration Method of Atomic Force Microscopy Image Based on Transfer Learning[J]. Acta Photonica Sinica, 2020, 49(4): 0410006 Copy Citation Text show less
    References

    [2] J S VILLARRUBIA. Algorithms for scanned probe microscope image simulation, surface reconstruction, and tip estimation. Journal of Research of the National Institute of Standards and Technology, 102, 425-454(1997).

    [3] D KELLER. Reconstruction of STM and AFM images distorted by finite-size tips. Surface Science, 253, 353-364(1991).

    [4] C HAHLWEG, M GRUHLKE, . Nonlinear distortion in atomic force microscopy(AFM) measurements. Measurement Science and Technology, 20, 084018(2009).

    [6] W L WANG, D J WHITEHOUSE. Application of neural networks to the reconstruction of scanning probe microscope images distorted by finite-size tips. Nanotechnology, 6, 45-51(1995).

    [7] P BAKUCZ, A YACOOT, T DZIOMBA. Neural network approximation of tip-abrasion effects in AFM imaging. Measurement Science and Technology, 19, 065101(2008).

    [8] WU Y, FANG Y, REN X, et al. Back propagation neural wks based hysteresis modeling compensation f a piezoelectric scanner[C].2016 IEEE International Conference on Manipulation, Manufacturing Measurement on the Nanoscale(3MNANO), IEEE, 2016: 119124.

    [9] HAHLWEG C, ROTHE H. Nonlinear disttions caused by AFMtip geometry limitations of reconstruction on discrete data[C].Instrumentation, Metrology, Stards f Nanomanufacturing Ⅲ, International Society f Optics Photonics, 2009, 7405: 74050K.

    [10] MENG Z, LI J, GONG Y. Adversarial featuremapping f speech enhancement[J]. arXiv preprint arXiv: 1809.02251, 2018.

    [11] CHAI X, BA Q, YANGG. acterizing robustness sensitivity of convolutional neural wks in segmentation of fluescence microscopy images[C].2018 25th IEEE International Conference on Image Processing(ICIP), IEEE, 2018: 38383842.

    [12] M H MODARRES, R AVERSA, . Neural network for nanoscience scanning electron microscope image recognition. Scientific Reports, 7, 13282(2017).

    [13] FU C, HO D J, HANS, et al. Nuclei segmentation of fluescence microscopy images using convolutional neural wks[C].2017 IEEE 14th International Symposium on Biomedical Imaging(ISBI 2017), IEEE, 2017: 704708.

    [15] S J PAN, Q YANG. A survey on transfer learning. IEEE Transactions on Knowledge and Data Engineering, 22, 1345-1359(2009).

    [16] HO D J, FU C, SALAMA P, et al. Nuclei detection segmentation of fluescence microscopy images using three dimensional convolutional neural wks[C].2018 IEEE 15th International Symposium on Biomedical Imaging(ISBI 2018), IEEE, 2018: 418422.

    [18] PITKÄAHO T, MANNINEN A, NAUGHTONT J. Focus classification in digital holographic microscopy using deep convolutional neural wks[C].European Conference on Biomedical Optics. Optical Society of America, 2017: 104140K.

    Jia-cheng HU, Di-xin YAN, Yu-shu SHI, Lu HUANG, Dong-sheng LI. Restoration Method of Atomic Force Microscopy Image Based on Transfer Learning[J]. Acta Photonica Sinica, 2020, 49(4): 0410006
    Download Citation