Searched for: subject%3A%22Semi%255C-supervised%255C+learning%22
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Jamshidi, A. (author), Faghih Roohi, S. (author), Nunez, Alfredo (author), Babuska, R. (author), De Schutter, B.H.K. (author), Dollevoet, R.P.B.J. (author), Li, Z. (author)
This paper develops a defect-based risk analysis methodology for estimating rail failure risk. The methodology relies on an evolution model addressing the severity level of rail surface defect, called squat. The risk of rail failure is assessed by analyzing squat failure probability using a probabilistic analysis of the squat cracks. For this...
conference paper 2016
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Hajizadeh, S. (author), Nunez, Alfredo (author), Tax, D.M.J. (author)
Rail defect detection by video cameras has recently gained much attention in both<br/>academia and industry. Rail image data has two properties. It is highly imbalanced towards the non-defective class and it has a large number of unlabeled data samples available for semisupervised learning techniques. In this paper we investigate if positive...
conference paper 2016