Covariate-Shift Generative Adversarial Network and Railway Track Image Analysis
Author:
Affiliation:
1. Doctoral Candidate, Dept. of Civil and Environmental Engineering, Univ. of Delaware, Newark, DE 19713.
2. Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, College Park, MD 20742 (corresponding author).
Publisher
American Society of Civil Engineers (ASCE)
Subject
Transportation,Civil and Structural Engineering
Link
https://ascelibrary.org/doi/pdf/10.1061/JTEPBS.TEENG-7390
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3. Balogun I. M. Leadingham D. Gulliot and N. Attoh-Okine. 2022. “Deep learning approach towards squat isolation in a multi-embedded track geometry defects.” In Proc. IEEE Int. Conf. on Big Data (Big Data). New York: IEEE.
4. Bhattarai B. S. Baek R. Bodur and T. Kyun Kim. 2020. “Sampling strategies for gan synthetic data.” In Proc. ICASSP IEEE Int. Conf. on Acoustics Speech and Signal Processing 2303–2307. New York: IEEE.
5. Pros and cons of GAN evaluation measures;Borji A.;Comput. Vis. Image Understanding,2019
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