30 citations · 37 across the 8 of their papers we have counts for
8 papers
Damping Identification Sensitivity in Flutter Speed Estimation
Gabriele Dessena, Alessandro Pontillo, Marco Civera +3
Predicting flutter remains a key challenge in aeroelastic research, with certain models relying on modal parameters, such as natural frequencies and damping ratios. These models ar…
A Paradigm Shift to Assembly-like Finite Element Model Updating
Gabriele Dessena, Alessandro Pontillo, Dmitry I. Ignatyev +2
In general, there is a mismatch between a finite element model {(FEM)} of a structure and its real behaviour. In aeronautics, this mismatch must be small because {FEM}s are a funda…
Relation3DMOT: Exploiting Deep Affinity for 3D Multi-Object Tracking from View Aggregation
Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos
Autonomous systems need to localize and track surrounding objects in 3D space for safe motion planning. As a result, 3D multi-object tracking (MOT) plays a vital role in autonomous…
Uncertainty Quantification of Multi-Scale Resilience in Nonlinear Complex Networks using Arbitrary Polynomial Chaos
Mengbang Zou, Luca Zanotti Fragonara, Weisi Guo
Resilience characterizes a system's ability to retain its original function when perturbations happen. In the past years our attention mainly focused on small-scale resilience, yet…
RoIFusion: 3D Object Detection from LiDAR and Vision
Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos
When localizing and detecting 3D objects for autonomous driving scenes, obtaining information from multiple sensor (e.g. camera, LIDAR) typically increases the robustness of 3D det…
Go Wider: An Efficient Neural Network for Point Cloud Analysis via Group Convolutions
Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos
In order to achieve better performance for point cloud analysis, many researchers apply deeper neural networks using stacked Multi-Layer-Perceptron (MLP) convolutions over irregula…
Fast Hierarchical Neural Network for Feature Learning on Point Cloud
Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos
The analyses relying on 3D point clouds are an utterly complex task, often involving million of points, but also requiring computationally efficient algorithms because of many real…
GAPNet: Graph Attention based Point Neural Network for Exploiting Local Feature of Point Cloud
Can Chen, Luca Zanotti Fragonara, Antonios Tsourdos
Exploiting fine-grained semantic features on point cloud is still challenging due to its irregular and sparse structure in a non-Euclidean space. Among existing studies, PointNet p…