[HTML][HTML] Street view imagery in urban analytics and GIS: A review
Street view imagery has rapidly ascended as an important data source for geospatial data
collection and urban analytics, deriving insights and supporting informed decisions. Such …
collection and urban analytics, deriving insights and supporting informed decisions. Such …
Machine learning for risk and resilience assessment in structural engineering: Progress and future trends
Population growth, economic development, and rapid urbanization in many areas have led
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
to increased exposure and vulnerability of structural and infrastructure systems to hazards …
Regional seismic risk and resilience assessment: Methodological development, applicability, and future research needs–An earthquake engineering perspective
Given the devastating losses incurred by past major earthquake events together with the
ever-increasing global seismic exposures due to population growth and urbanization …
ever-increasing global seismic exposures due to population growth and urbanization …
Understanding architecture age and style through deep learning
Architectural styles and their evolution are central to architecture history. However,
traditional approaches to understand styles and their evolution require domain expertise …
traditional approaches to understand styles and their evolution require domain expertise …
[HTML][HTML] Towards a 'resource cadastre'for a circular economy–urban-scale building material detection using street view imagery and computer vision
The lack of data on existing buildings hinders efforts towards repair, reuse, and recycling of
materials, which are crucial for mitigating the climate crisis. Manual acquisition of building …
materials, which are crucial for mitigating the climate crisis. Manual acquisition of building …
A review of the research and application of deep learning-based computer vision in structural damage detection
Z Lingxin, S Junkai, Z Baijie - Earthquake engineering and engineering …, 2022 - Springer
Damage detection is a key procedure in maintenance throughout structures' life cycles and
post-disaster loss assessment. Due to the complex types of structural damages and the low …
post-disaster loss assessment. Due to the complex types of structural damages and the low …
Machine learning-based regional scale intelligent modeling of building information for natural hazard risk management
The intensity of many natural hazards, such as hurricanes, floods, tornadoes, etc., are
increasing as a consequence of climate change. This increase in intensity coupled with the …
increasing as a consequence of climate change. This increase in intensity coupled with the …
Street View Imagery (SVI) in the built environment: A theoretical and systematic review
Y Li, L Peng, C Wu, J Zhang - Buildings, 2022 - mdpi.com
Street view imagery (SVI) provides efficient access to data that can be used to research
spatial quality at the human scale. The previous reviews have mainly focused on specific …
spatial quality at the human scale. The previous reviews have mainly focused on specific …
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 …
stock for potential structural defects is one way to locate structures that are vulnerable to …
Deep learning–based building attribute estimation from google street view images for flood risk assessment using feature fusion and task relation encoding
Floods are the most common and damaging natural disaster worldwide in terms of both
economic losses and human casualties. Currently, policymakers rely on data collected …
economic losses and human casualties. Currently, policymakers rely on data collected …