Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks
Hyeonho Kim, Seokmin Han, Journal of Internet Computing and Services, Vol. 21, No. 6, pp. 23-31, Dec. 2020
10.7472/jksii.2020.21.6.23, Full Text:
Keywords: Railroad surface, Generative Adversarial Network, Image Representation, Conditional generation model, Detection Model
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Cite this article
[APA Style]
Kim, H. & Han, S. (2020). Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks. Journal of Internet Computing and Services, 21(6), 23-31. DOI: 10.7472/jksii.2020.21.6.23.
[IEEE Style]
H. Kim and S. Han, "Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks," Journal of Internet Computing and Services, vol. 21, no. 6, pp. 23-31, 2020. DOI: 10.7472/jksii.2020.21.6.23.
[ACM Style]
Hyeonho Kim and Seokmin Han. 2020. Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks. Journal of Internet Computing and Services, 21, 6, (2020), 23-31. DOI: 10.7472/jksii.2020.21.6.23.