226 citations · 863 across the 35 of their papers we have counts for
10 papers · 1 filter
How Sampling Strategy Affects Imbalance Mitigation in LiDAR Segmentation: A Study of Structured vs. Random Point-Based Architectures
Antonis Savva, Christos Kyrkou, Theocharis Theocharides
Class imbalance in LiDAR point clouds poses challenges for semantic segmentation in autonomous navigation and urban mapping. While 2D vision has numerous mitigation techniques, the…
Loss Landscape Topology Reveals Why Simple Baselines are Competitive at 3D Point Cloud Segmentation Under Class Imbalance
Antonis Savva, Christos Kyrkou, Theocharis Theocharides
Semantic segmentation of 3D point clouds faces severe class imbalance, yet the effectiveness of specialized imbalance-aware methods from 2D computer vision remains unclear in 3D co…
Efficient Global Neural Architecture Search
Shahid Siddiqui, Christos Kyrkou, Theocharis Theocharides
Neural architecture search (NAS) has shown promise towards automating neural network design for a given task, but it is computationally demanding due to training costs associated w…
DriveGuard: Robustification of Automated Driving Systems with Deep Spatio-Temporal Convolutional Autoencoder
Andreas Papachristodoulou, Christos Kyrkou, Theocharis Theocharides
Autonomous vehicles increasingly rely on cameras to provide the input for perception and scene understanding and the ability of these models to classify their environment and objec…
EmergencyNet: Efficient Aerial Image Classification for Drone-Based Emergency Monitoring Using Atrous Convolutional Feature Fusion
Christos Kyrkou, Theocharis Theocharides
Deep learning-based algorithms can provide state-of-the-art accuracy for remote sensing technologies such as unmanned aerial vehicles (UAVs)/drones, potentially enhancing their rem…
Extracting the fundamental diagram from aerial footage
Rafael Makrigiorgis, Panayiotis Kolios, Stelios Timotheou +2
Efficient traffic monitoring is playing a fundamental role in successfully tackling congestion in transportation networks. Congestion is strongly correlated with two measurable cha…
EdgeNet: Balancing Accuracy and Performance for Edge-based Convolutional Neural Network Object Detectors
George Plastiras, Christos Kyrkou, Theocharis Theocharides
Visual intelligence at the edge is becoming a growing necessity for low latency applications and situations where real-time decision is vital. Object detection, the first step in v…
Efficient ConvNet-based Object Detection for Unmanned Aerial Vehicles by Selective Tile Processing
George Plastiras, Christos Kyrkou, Theocharis Theocharides
Many applications utilizing Unmanned Aerial Vehicles (UAVs) require the use of computer vision algorithms to analyze the information captured from their on-board camera. Recent adv…
Deep-Learning-Based Aerial Image Classification for Emergency Response Applications Using Unmanned Aerial Vehicles
Christos Kyrkou, Theocharis Theocharides
Unmanned Aerial Vehicles (UAVs), equipped with camera sensors can facilitate enhanced situational awareness for many emergency response and disaster management applications since t…
DroNet: Efficient convolutional neural network detector for real-time UAV applications
Christos Kyrkou, George Plastiras, Stylianos Venieris +2
Unmanned Aerial Vehicles (drones) are emerging as a promising technology for both environmental and infrastructure monitoring, with broad use in a plethora of applications. Many su…