Personal profile
Author IDs
ORCID iD: 0000-0003-3197-5460
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Dive into the research topics where Yuanyuan TIAN is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations from the last five years
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Research output
- 4 RGC 21 - Publication in refereed journal
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Lightweight deep learning framework for recognizing construction workers' activities based on simplified node combinations
Tian, Y., Chen, J., Kim, J. I. & Kim, J., Feb 2024, In: Automation in Construction. 158, 105236.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
6 Link opens in a new tab Citations (Scopus) -
Multiple-input streams attention (MISA) network for skeleton-based construction workers' action recognition using body-segment representation strategies
Tian, Y., Chen, J., Kim, J. I. & Kwac, J., Dec 2023, In: Automation in Construction. 156, 105104.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
5 Link opens in a new tab Citations (Scopus) -
Multi-Stream Fusion Network for Skeleton-Based Construction Worker Action Recognition
Tian, Y., Liang, Y., Yang, H. & Chen, J., Dec 2023, In: Sensors. 23, 23, 9350.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Open AccessFile3 Link opens in a new tab Citations (Scopus)38 Downloads (CityUHK Scholars) -
Construction motion data library: an integrated motion dataset for on-site activity recognition
Tian, Y., Li, H., Cui, H. & Chen, J., 2022, In: Scientific Data. 9, 726.Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Open AccessFile25 Link opens in a new tab Citations (Scopus)62 Downloads (CityUHK Scholars)
Thesis
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Deep Learning-based Activity Recognition Framework for On-site Construction Workers
TIAN, Y. (Author), CHEN, J. (Supervisor) & KIM, J. I. (Supervisor), 31 Aug 2023Student thesis: Doctoral Thesis