Zobrazeno 1 - 10
of 171
pro vyhledávání: '"Scherer, Raimar"'
Semantic segmentation profits from deep learning and has shown its possibilities in handling the graphical data from the on-site inspection. As a result, visual damage in the facade images should be detected. Attention mechanism and generative advers
Externí odkaz:
http://arxiv.org/abs/2209.13283
To improve the efficiency and reduce the labour cost of the renovation process, this study presents a lightweight Convolutional Neural Network (CNN)-based architecture to extract crack-like features, such as cracks and joints. Moreover, Transfer Lear
Externí odkaz:
http://arxiv.org/abs/2105.10892
Structures suffer from the emergence of cracks, therefore, crack detection is always an issue with much concern in structural health monitoring. Along with the rapid progress of deep learning technology, image semantic segmentation, an active researc
Externí odkaz:
http://arxiv.org/abs/2104.14586
Autor:
Hamdan, Al-Hakam, Taraben, Jakob, Helmrich, Marcel, Mansperger, Tobias, Morgenthal, Guido, Scherer, Raimar J.
Publikováno v:
In Automation in Construction August 2021 128
Autor:
Lin, Fangzheng, Scherer, Raimar J.
Publikováno v:
In Automation in Construction November 2020 119
Publikováno v:
EPTCS 83, 2012, pp. 1-9
During the execution of large scale construction projects performed by Virtual Organizations (VO), relatively complex technical models have to be exchanged between the VO members. For linking the trade and transfer of these models, a so-called multi-
Externí odkaz:
http://arxiv.org/abs/1204.6089
Publikováno v:
In Advanced Engineering Informatics October 2018 38:54-66
Autor:
Fuchs, Sebastian, Scherer, Raimar J.
Publikováno v:
In Automation in Construction March 2017 75:22-32