2019 IEEE 8th Global Conference on Consumer Electronics (GCCE) 2019
DOI: 10.1109/gcce46687.2019.9015437
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Weakly Supervised Approach to Defect Detection in Concrete Structures Using Hammering Test

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Cited by 8 publications
(12 citation statements)
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“…This is certainly due to the higher number of clusters since the two blocks were from different batches and defect types also vary. Without visual information, while the consistency of output was slightly increased by our proposed active query scheme compared to Louhi Kasahara et al [14], the average performance slightly decreased. However, since the addition of visual information allows the proposed method to outperform the method of Louhi Kasahara et al [15], it can be strongly suspected that the nature of errors was different when using the proposed active query scheme: those errors were easier to compensate for by the spatial estimator.…”
Section: Resultsmentioning
confidence: 68%
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“…This is certainly due to the higher number of clusters since the two blocks were from different batches and defect types also vary. Without visual information, while the consistency of output was slightly increased by our proposed active query scheme compared to Louhi Kasahara et al [14], the average performance slightly decreased. However, since the addition of visual information allows the proposed method to outperform the method of Louhi Kasahara et al [15], it can be strongly suspected that the nature of errors was different when using the proposed active query scheme: those errors were easier to compensate for by the spatial estimator.…”
Section: Resultsmentioning
confidence: 68%
“…The methods of Louhi Kasahara et al [14] and Louhi Kasahara et al [15] were weakly supervised. Louhi Kasahara et al [14] only used weak supervision, as opposed to Louhi Kasahara et al [15] and the proposed method that use position information to complement weak supervision. The method of Louhi Kasahara et al [15] assumed that the human user would randomly select pairs of samples for weak supervision.…”
Section: Our Novelty and Overview Of Proposed Methodsmentioning
confidence: 99%
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