General Session

[General Session] D. Damage investigation and analysis, etc. » D-5 Machine learning/IoT/DX

Machine learning / IoT / DX (1)

Sat. Nov 25, 2023 2:00 PM - 3:30 PM G416 (PACIFICO Yokohama North, 4F)

Chairperson: Dang Ji (Saitama University)

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2:00 PM - 2:12 PM

[Day3-G416-13] Development of A Damage Detection Method for Wooded Buildings by Instance Segmentation

*Yohei UEOKA¹, Satoshi TANAKA² (1. Mikuniya Co., 2. Graduate School of Environment and Disaster Research, Tokoha University.)

2:13 PM - 2:25 PM

[Day3-G416-14] Construction of a repair estimation calculation system for determining
damage to residential buildings using AI

*Taiga Shibata¹, Muneyoshi Numada¹ (1. University of Tokyo Institute of Production Technology)

2:26 PM - 2:38 PM

[Day3-G416-15] Earthquake damage detection and level classification method based on convolutional neural network using onsite photographs of the Kumamoto Earthquake

*Kai Wu¹, Masashi Matsuoka¹, Haruki Oshio¹ (1. Tokyo Institute of Technology)

2:39 PM - 2:51 PM

[Day3-G416-16] Building Damage Assessment Model Using AI and Damage Rate Evaluation by Video from Vehicle-mounted Camera

*Kota Osasa¹, Keisuke Kato¹, Yuya Takase¹, Tadayoshi Nakashima² (1. Muroran Institute of Technology, 2. Hokkaido University)

2:52 PM - 3:04 PM

[Day3-G416-17] Analysis of the Relationship Between the Accuracy of Damage Estimation Using Deep Learning Models Based on Seismic Response Analysis Results and Seismic Ground Motion

*Atsushi Aoi¹, Nyamkhuu Ganbat², Hiroshi Tsunekawa¹, Mutsuhiro Yoshizawa¹, Atsushi Kanbayashi¹, Tomonori Hashiyama² (1. Takenaka Corporation, 2. The University of Electro-Communications)

3:05 PM - 3:17 PM

[Day3-G416-18] Machine Learning-Based Seismic Damage Prediction of Buildings at a Regional Scale

*Sanjeev Bhatta¹, Xiandong Kang², Ji Dang¹ (1. Saitama University, 2. Beijing earthquake agency )

3:18 PM - 3:30 PM

[Day3-G416-19] RECOGNITION OF DAMAGES FROM WAVE PROPAGATION BETWEEN TWO ADJACENT FLOORS USING CNN

*Aijia Zhang¹, Xin Wang², Ji Dang¹ (1. Saitama University, 2. Ashikaga University)

Session information

Machine learning / IoT / DX (1)

[Day3-G416-13] Development of A Damage Detection Method for Wooded Buildings by Instance Segmentation

[Day3-G416-14] Construction of a repair estimation calculation system for determining
damage to residential buildings using AI

[Day3-G416-15] Earthquake damage detection and level classification method based on convolutional neural network using onsite photographs of the Kumamoto Earthquake

[Day3-G416-16] Building Damage Assessment Model Using AI and Damage Rate Evaluation by Video from Vehicle-mounted Camera

[Day3-G416-17] Analysis of the Relationship Between the Accuracy of Damage Estimation Using Deep Learning Models Based on Seismic Response Analysis Results and Seismic Ground Motion

[Day3-G416-18] Machine Learning-Based Seismic Damage Prediction of Buildings at a Regional Scale

[Day3-G416-19] RECOGNITION OF DAMAGES FROM WAVE PROPAGATION BETWEEN TWO ADJACENT FLOORS USING CNN

Authentication

Session information

Machine learning / IoT / DX (1)

[Day3-G416-13] Development of A Damage Detection Method for Wooded Buildings by Instance Segmentation

[Day3-G416-14] Construction of a repair estimation calculation system for determiningdamage to residential buildings using AI

[Day3-G416-15] Earthquake damage detection and level classification method based on convolutional neural network using onsite photographs of the Kumamoto Earthquake

[Day3-G416-16] Building Damage Assessment Model Using AI and Damage Rate Evaluation by Video from Vehicle-mounted Camera

[Day3-G416-17] Analysis of the Relationship Between the Accuracy of Damage Estimation Using Deep Learning Models Based on Seismic Response Analysis Results and Seismic Ground Motion

[Day3-G416-18] Machine Learning-Based Seismic Damage Prediction of Buildings at a Regional Scale

[Day3-G416-19] RECOGNITION OF DAMAGES FROM WAVE PROPAGATION BETWEEN TWO ADJACENT FLOORS USING CNN

Authentication

[Day3-G416-14] Construction of a repair estimation calculation system for determining
damage to residential buildings using AI