Expertises
Engineering & Materials Science
# Defects
# Drainage
# Inspection
# Networks (Circuits)
# Pipe
# Productivity
# Sewers
# Television
Verbonden aan
Publicaties
Recent
Yin, X., & Wang, M. (2022).
Science Mapping for Recent Research Regarding Urban Underground Infrastructure.
Buildings.
https://doi.org/10.3390/buildings12112031
Xiao, B.
, Chen, C.
, & Yin, X. (2022).
Recent advancements of robotics in construction.
Automation in construction,
144, [104591].
https://doi.org/10.1016/j.autcon.2022.104591
Li, L., Luan, H.
, Yin, X., Dou, Y., Yuan, M., & Li, Z. (2022).
Understanding Sustainability in Off-Site Construction Management: State of the Art and Future Directions.
Journal of construction engineering and management,
148(11), [03122008].
https://doi.org/10.1061/(ASCE)CO.1943-7862.0002396
Karabij, M.
, Yin, X., Bouferguene, A., & Al-Hussein, M. (2022).
Image Processing–Based Framework for Determining Deterioration in Sewer Pipe Defects.
Journal of Infrastructure Systems,
28(4).
https://doi.org/10.1061/(ASCE)IS.1943-555X.0000713
Wang, M.
, & Yin, X. (2022).
Construction and maintenance of urban underground infrastructure with digital technologies.
Automation in construction,
141, [104464].
https://doi.org/10.1016/j.autcon.2022.104464
Zhang, N., Wang, J., Al-Hussein, M.
, & Yin, X. (2022).
BIM-based automated design of drainage systems for panelized residential buildings.
International journal of construction management.
https://doi.org/10.1080/15623599.2022.2085853
Yuan, M., Li, Z., Li, X., Luo, X.
, Yin, X., & Cai, J. (2021).
Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry.
Engineering, Construction and Architectural Management.
https://doi.org/10.1108/ECAM-07-2021-0613
Xiao, B., Zhang, Y., Chen, Y.
, & Yin, X. (2021).
A semi-supervised learning detection method for vision-based monitoring of construction sites by integrating teacher-student networks and data augmentation.
Advanced engineering informatics,
50, [101372].
https://doi.org/10.1016/j.aei.2021.101372
Xiao, B.
, Yin, X., & Kang, S-C. (2021).
Vision-based method of automatically detecting construction video highlights by integrating machine tracking and CNN feature extraction.
Automation in construction,
129, [103817].
https://doi.org/10.1016/j.autcon.2021.103817
Yin, X., Ma, T., Bouferguene, A., & Al-Hussein, M. (2021).
Automation for sewer pipe assessment: CCTV video interpretation algorithm and sewer pipe video assessment (SPVA) system development.
Automation in construction,
125, [103622].
https://doi.org/10.1016/j.autcon.2021.103622
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Verbonden aan Opleidingen
Bachelor
Master
Vakken Collegejaar 2022/2023
Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.
Vakken Collegejaar 2021/2022
Contactgegevens
Bezoekadres
Universiteit Twente
Faculty of Engineering Technology
Horst Complex
(gebouwnr. 20), kamer Z208
De Horst 2
7522LW Enschede
Postadres
Universiteit Twente
Faculty of Engineering Technology
Horst Complex
Z208
Postbus 217
7500 AE Enschede