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Multiple Oracle consensus for weakly supervised defect detection in concrete structures using audio data
Advanced Robotics ( IF 2 ) Pub Date : 2020-12-22 , DOI: 10.1080/01691864.2020.1861977
Jun Younes Louhi Kasahara 1 , Atsushi Yamashita 1 , Hajime Asama 1
Affiliation  

ABSTRACT

Inspection of critical social infrastructures, which are mainly made of concrete, is a pressing issue. Weakly supervised methods are interesting for such critical tasks because they allow a unique mix of human involvement and automation. However, humans can make mistakes, resulting in the system being misled. In the present paper is proposed a framework for weakly supervised defect detection in concrete structures involving a consensus between several humans providing weak supervision. This allows to compensate for the shortcomings of each individual human and, therefore, yield better performance along with robustness to erroneous weak supervision. Experiments conducted with concrete test blocks in laboratory conditions showed the effectiveness of our proposed method.



中文翻译:

使用音频数据在混凝土结构中进行弱监督缺陷检测的多个Oracle共识

摘要

对主要由混凝土制成的关键社会基础设施的检查是一个紧迫的问题。监督不足的方法对于此类关键任务很有趣,因为它们允许人工参与和自动化的独特组合。但是,人会犯错,导致系统被误导。本文提出了一种在混凝土结构中进行弱监督缺陷检测的框架,该框架涉及多个提供弱监督的人员之间的共识。这可以弥补每个人的缺点,因此,可以产生更好的性能以及对错误的弱监督的鲁棒性。在实验室条件下用混凝土试块进行的实验证明了我们提出的方法的有效性。

更新日期:2021-02-09
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