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5. M. Elleuch, N. Tagougui, M. Kherallah, Optimization of DBN using regularization methods
applied for recognizing arabic handwritten script. Procedia Comput. Sci. 108(6), 2292–2297
(2017)
6. G. Lipeng, L. Yong, Research on gear fault diagnosis based on the combination of isometric
mapping and DBN. J. Mech. Strength 41(05), 1029–1034 (2019)
7. L. Chunliu, Z. Zheng, Application of improved depth confidence network in urban water
consumption prediction. Software Guide 11, 1–6 (2019)
8. M. Elleuch, N. Tagougui, M. Kherallah, Optimization of DBN using regularization methods
applied for recognizing Arabic handwritten script. Procedia Comput. Sci. 108, 2292–2297
(2018)
9. W. Fang, W. Yuangen, L. Lin, Feasibility study on Dr detection of urban gas pipeline. Pipeline
Technique Equipment 05, 58–62 (2019)
10. A. R. Triki, M. B. Blaschko, Y. M. Jung, S. Song, H. J. Han, Intraoperative margin assessment
of human breast tissue in optical coherence tomography images using deep neural networks.
Computerized Med Imaging Graph 69, 21–32 (2018)
11. W. Jianye, W. Huijie, Z. Guangrao, Damaged corrosion on the buried steel gas pipeline corrosion
leakage detection and corrective. Total Corrosion Control 33(04), 102–106 (2019)
12. W. Xinying, J. Zhiwei, Research on multi-information fusion urban gas pipeline leakage
diagnosis technology. China Saf. Sci. J. 24(6), 165–171 (2014)
13. F. N. Varela, M. Y. Tan, M. Forsyth, A novel approach for monitoring pipeline corrosion under
disbonded coatings, in 2014 10th International Pipeline Conference (2014)
W. Xinying et al.
4. Q. Wang, W. Zhou, A new burst pressure model for thin-walled pipe elbows containing metalloss corrosion defects. Eng. Struct. 200(109720) (2019)
5. M. Elleuch, N. Tagougui, M. Kherallah, Optimization of DBN using regularization methods
applied for recognizing arabic handwritten script. Procedia Comput. Sci. 108(6), 2292–2297
(2017)
6. G. Lipeng, L. Yong, Research on gear fault diagnosis based on the combination of isometric
mapping and DBN. J. Mech. Strength 41(05), 1029–1034 (2019)
7. L. Chunliu, Z. Zheng, Application of improved depth confidence network in urban water
consumption prediction. Software Guide 11, 1–6 (2019)
8. M. Elleuch, N. Tagougui, M. Kherallah, Optimization of DBN using regularization methods
applied for recognizing Arabic handwritten script. Procedia Comput. Sci. 108, 2292–2297
(2018)
9. W. Fang, W. Yuangen, L. Lin, Feasibility study on Dr detection of urban gas pipeline. Pipeline
Technique Equipment 05, 58–62 (2019)
10. A. R. Triki, M. B. Blaschko, Y. M. Jung, S. Song, H. J. Han, Intraoperative margin assessment
of human breast tissue in optical coherence tomography images using deep neural networks.
Computerized Med Imaging Graph 69, 21–32 (2018)
11. W. Jianye, W. Huijie, Z. Guangrao, Damaged corrosion on the buried steel gas pipeline corrosion
leakage detection and corrective. Total Corrosion Control 33(04), 102–106 (2019)
12. W. Xinying, J. Zhiwei, Research on multi-information fusion urban gas pipeline leakage
diagnosis technology. China Saf. Sci. J. 24(6), 165–171 (2014)
13. F. N. Varela, M. Y. Tan, M. Forsyth, A novel approach for monitoring pipeline corrosion under
disbonded coatings, in 2014 10th International Pipeline Conference (2014)