Conventional RVS methods for seismic risk assessment for estimating the current situation of existing buildings: A state-of-the-art review

N Bektaş, O Kegyes-Brassai - Sustainability, 2022 - mdpi.com
Developments in the field of earthquake engineering over the past few decades have
contributed to the development of new methods for evaluating the risk levels in buildings …

A review on application of soft computing techniques for the rapid visual safety evaluation and damage classification of existing buildings

E Harirchian, SEA Hosseini, K Jadhav, V Kumari… - Journal of Building …, 2021 - Elsevier
Seismic vulnerability assessment of existing buildings is of great concern around the world.
Different countries develop various approaches and methodologies to overcome the …

Automatic detection of unreinforced masonry buildings from street view images using deep learning-based image segmentation

C Wang, SE Antos, LM Triveno - Automation in Construction, 2021 - Elsevier
Mitigation of seismic risk is a challenge for 70+ countries in the world. Screening the building
stock for potential structural defects is one way to locate structures that are vulnerable to …

Develo** a hierarchical type-2 fuzzy logic model to improve rapid evaluation of earthquake hazard safety of existing buildings

E Harirchian, T Lahmer - Structures, 2020 - Elsevier
The demand for develo** a rapid, reliable, and effective technique for prioritizing the
buildings with high seismic vulnerability and assisting disaster mitigation in develo** post …

ML-EHSAPP: A prototype for machine learning-based earthquake hazard safety assessment of structures by using a smartphone app

E Harirchian, K Jadhav, V Kumari… - European Journal of …, 2022 - Taylor & Francis
The recent devastating earthquakes have caused severe physical, social, and financial
damage worldwide and indicate that many existing buildings, especially in develo** …

A machine learning framework for assessing seismic hazard safety of reinforced concrete buildings

E Harirchian, V Kumari, K Jadhav, R Raj Das… - Applied Sciences, 2020 - mdpi.com
Although averting a seismic disturbance and its physical, social, and economic disruption is
practically impossible, using the advancements in computational science and numerical …

A synthesized study based on machine learning approaches for rapid classifying earthquake damage grades to RC buildings

E Harirchian, V Kumari, K Jadhav, S Rasulzade… - Applied Sciences, 2021 - mdpi.com
A vast number of existing buildings were constructed before the development and
enforcement of seismic design codes, which run into the risk of being severely damaged …

Rapid visual screening of soft-story buildings from street view images using deep learning classification

Q Yu, C Wang, F McKenna, SX Yu, E Taciroglu… - Earthquake Engineering …, 2020 - Springer
Rapid and accurate identification of potential structural deficiencies is a crucial task in
evaluating seismic vulnerability of large building inventories in a region. In the case of multi …

Adaln: a vision transformer for multidomain learning and predisaster building information extraction from images

Y Guo, C Wang, SX Yu, F McKenna… - Journal of Computing in …, 2022 - ascelibrary.org
Satellite and street view images are widely used in various disciplines as a source of
information for understanding the built environment. In natural hazard engineering, high …

Assessment of seismic building vulnerability using rapid visual screening method through web-based application for Malaysia

MM Kassem, S Beddu, JH Ooi, CG Tan… - Buildings, 2021 - mdpi.com
Rapid visual screening is a quick and simple approach often used by researchers to
estimate the seismic vulnerability of buildings in an area. In this study, preliminary seismic …