111 citations · 240 across the 29 of their papers we have counts for
7 papers · 1 filter
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…
Threshold Greedy Based Task Allocation for Multiple Robot Operations
Teng Li, Hyo-Sang Shin, Antonios Tsourdos
This paper deals with large-scale decentralised task allocation problems for multiple heterogeneous robots with monotone submodular objective functions. One of the significant chal…
A Domain-Knowledge-Aided Deep Reinforcement Learning Approach for Flight Control Design
Hyo-Sang Shin, Shaoming He, Antonios Tsourdos
This paper aims to examine the potential of using the emerging deep reinforcement learning techniques in flight control. Instead of learning from scratch, we suggest to leverage do…
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…
Sample Greedy Gossip for Distributed Network-Wide Average Computation
Hyo-Sang Shin, Shaoming He, Antonios Tsourdos
This paper investigates the problem of distributed network-wide averaging and proposes a new greedy gossip algorithm. Instead of finding the optimal path of each node in a greedy m…