Giảng viên Trần Văn Phúc
Đồng thời công tác tại: Trường Đại học Sejong và IRIS Technology company, Hàn Quốc
Năm sinh: 1984
Học vị cao nhất: Tiến sĩ
Quá trình đào tạo:
- Tiến sĩ Kỹ thuật xây dựng – Đại học Sejong, Hàn Quốc
- Thạc sĩ Kỹ thuật xây dựng – Trường Đại học Bách Khoa TP. Hồ Chí Minh
- Đại học – Trường Đại học Giao thông vận tải TP. Hồ Chí Minh
Research works
– Applying Deep learning and Machine learning for object detection.
– Applying Big data for Pavement Management System.
– Overlay pavement design, pavement material.
– Structural analysis and modelling of asphalt concrete.
Skills
Data: Artificial Intelligence (AI), Machine learning, Deep learning, CNN
Software: Abaqus, SAP, Plaxis, Autocad, Roadplan, MEPDG, Kenpave, MS Office
Programming: Python, Matlab, Excel, VBA
Languages: English, Vietnamese
Publications
2018
Investigation of Different Approach in Evaluating Moisture Damage Resistance of Asphalt Mixtures.
TC Do, VP Tran, HJ Lee, WJ Kim
International Conference of Korean Society of Road Engineers.
2019
Mechanical characteristics of tensile strength ratio method compared to other parameters used for moisture susceptibility evaluation of as-phalt mixtures.
TC Do, VP Tran, HJ Lee, WJ Kim
Journal of Traffic and Transportation Engineering.
2020
Application of Deep Learning Algorithm for Pavement Object Detection; Part 1: Asphalt Pavement Crack Detection; Part 2: Cavity Detection.
PhD Thesis, Sejong University.
2020
One stage detector (RetinaNet)-based crack detection for asphalt pavements considering pavement distresses and surface objects.
VP Tran, TS Tran, HJ Lee, KD Kim, J Baek, TT Nguyen
Journal of Civil Structural Health Monitoring, Springer.
2020
A two-step sequential automated crack detection and severity classification process for asphalt pavements.
TS Tran, VP Tran, HJ Lee, JM Flores, VP Le
International Journal of Pavement Engineering, Taylor and Francis.
2020
Crack detection for asphalt pavement using deep learning based Faster R-CNN.
The 2020 International Conference on Application of Artificial Intelligence in Transportation Ho Chi Minh City, Vietnam.
2021
Automation asphalt pavement distress detection using deep learning-based retinanet.
Van Phuc Tran, Thai Son Tran, Van Phuc Le, Hyun Jong Lee
Journal of Transportation Science and Technology.
2022
AI-based Pavement Distress Evaluation and Network-Level Pavement Management Considering Homogenized Sections.
TS Tran, HJ Lee, H Kim, K Kim, VP Tran, SD Nguyen, J Lee, J Song
Korea Road Association conference.
2022
Deep Learning-Based Crack Detection: A Survey.
SD Nguyen, TS Tran, VP Tran, HJ Lee, MJ Piran, VP Le
International Journal of Pavement Research and Technology.
2022
Automated Segmentation and Deterioration Determination of Road Markings.
SD Nguyen, VP Tran, TS Tran, HJ Lee, JM Flores
Journal of Transportation Engineering, Part B: Pavements.
2023
GAN–XGB–cavity: automated estimation of underground cavities’properties using GPR data.
VP Tran, SD Nguyen, HJ Lee, TS Tran, C Elipse
Neural Computing and Applications.
2023
Advanced crack detection and segmentation on bridge decks using deep learning.
TS Tran, SD Nguyen, HJ Lee, VP Tran
Construction and Building Materials.
2023
Automated analysis of GPR data for accurate underground cavity property estimation.
SD Nguyen, VP Tran, TS Tran, HJ Lee
International Conference on Sustainable Development and Climate Change Adaptation in Transportation 2023.