Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

We propose a semantic shape editing method to edit 3D triangle meshes using parametric implicit surface templates, benefiting from the many advantages offered by analytical implicit representations, such as infinite resolution and boolean or blending opera ...

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Currently, post-earthquake assessment is performed visually, which implies that inspectors visit the damaged buildings and, based on their expertise, assign a damage grade. Yet, visual inspection is subjective, time-consuming and difficult to document. In ...

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...

This paper discusses the cyclic performance of a heavily instrumented 2-bay full-scale composite-steel moment resisting frame (CMRF) sub-system from the onset of structural damage up until incipient collapse. The CMRF featured stiffened end plate bolted co ...

Non-Bayesian social learning is a framework for distributed hypothesis testing aimed at learning the true state of the environment. Traditionally, the agents are assumed to receive observations conditioned on the same true state, although it is also possib ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world. This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR. At the advent of ...

The optical domain presents potential avenues for enhancing both computing and communication due to its inherent properties of bandwidth, parallelism, and energy efficiency. This research focuses on harnessing 3-Dimensional (3D) diffractive optics for nove ...

Masonry buildings form building aggregates around the world in historical centers, which developed as the layout of the city or village densified. In these aggregates, adjacent buildings can share structural walls, connected at the interfaces by interlocki ...

Masonry aggregates, which emerged as layouts of cities and villages became denser, make up historical centres all over the world. In these aggregates, neighbouring structures may share structural walls that are joined at the interfaces by mortar or interlo ...

Many approaches to draping individual garments on human body models are realistic, fast, and yield outputs that are differentiable with respect to the body shape on which they are draped. However, they are either unable to handle multi-layered clothing, wh ...

The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

With the overall goal of reducing the numerical burden of uncertainty quantification involved in seismic risk assessments, this paper examines opportunities for assessment of seismic collapse capacity and risk using data-driven surrogates as a complement t ...

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

This work presents the initial studies on the requirements for the design of 3D coils on EU-DEMO. The use of 3D coils in present machines includes two main purposes: the first one is the Error Field Correction (EFC). The EFC aims at minimizing the intrinsi ...

Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling

Chattez avec Graph Search

Semantic Shape Editing with Parametric Implicit Templates

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Incorporating Projective Geometry into Deep Learning

Towards real-time digital twins for post-earthquake damage assessment of masonry buildings

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

Full Scale Experiments of a Composite Steel Moment Resisting Frame: Behavioral Insights and Implications on Seismic Design

Detection of Malicious Agents in Social Learning

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Enabling Uncertainty Estimation in Iterative Neural Networks

From finger animation to full-body embodiment of avatars with different morphologies and proportions

3D diffractive optics for linear interconnects and nonlinear processing

Seismic Testing of Adjacent Interacting Masonry Structures

Seismic Testing of Adjacent Interacting Masonry Structures – Analysis of a Blind Prediction

ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns

Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

Surrogate modelling for seismic collapse risk assessment of steel moment resisting frames

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Studies on EU-DEMO 3D coils requirements and conceptual design for error field correction and plasma control