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Kang, Z. (author), Yang, Juntao (author), Zhong, Ruofei (author), Wu, Yongxing (author), Shi, Zhenwei (author), Lindenbergh, R.C. (author)
The digital mapping of road environment is an important task for road infrastructure inventory and urban planning. Automatic extraction and classification of pole-like objects can remarkably reduce mapping cost and enhance work efficiency. Therefore, this paper proposes a voxel-based method that automatically extracts and classifies three...
journal article 2018
document
Qu, Dingran (author), Qiao, Tiezhu (author), Pang, Y. (author), Yang, Yi (author), Zhang, Haitao (author)
Belt conveyor is considered as a momentous component of modern coal mining transportation system, and thus it is an essential task to diagnose and monitor the damage of belt in real time and accurately. Based on the deep learning algorithm, this present study proposes a method of conveyor belt damage detection based on ADCN (Adaptive Deep...
journal article 2021
document
Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)
Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...
journal article 2022