226 citations · 591 across the 15 of their papers we have counts for
15 papers
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…
Convolutional Channel-wise Competitive Learning for the Forward-Forward Algorithm
Andreas Papachristodoulou, Christos Kyrkou, Stelios Timotheou +1
The Forward-Forward (FF) Algorithm has been recently proposed to alleviate the issues of backpropagation (BP) commonly used to train deep neural networks. However, its current form…
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…
C^3Net: End-to-End deep learning for efficient real-time visual active camera control
Christos Kyrkou
The need for automated real-time visual systems in applications such as smart camera surveillance, smart environments, and drones necessitates the improvement of methods for visual…
Fast and Accurate Quantized Camera Scene Detection on Smartphones, Mobile AI 2021 Challenge: Report
Andrey Ignatov, Grigory Malivenko, Radu Timofte +28
Camera scene detection is among the most popular computer vision problem on smartphones. While many custom solutions were developed for this task by phone vendors, none of the desi…
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…
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead
Muhammad Shafique, Mahum Naseer, Theocharis Theocharides +4
Machine Learning (ML) techniques have been rapidly adopted by smart Cyber-Physical Systems (CPS) and Internet-of-Things (IoT) due to their powerful decision-making capabilities. Ho…
Imitation-Based Active Camera Control with Deep Convolutional Neural Network
Christos Kyrkou
The increasing need for automated visual monitoring and control for applications such as smart camera surveillance, traffic monitoring, and intelligent environments, necessitates t…
YOLOpeds: Efficient Real-Time Single-Shot Pedestrian Detection for Smart Camera Applications
Christos Kyrkou
Deep Learning-based object detectors can enhance the capabilities of smart camera systems in a wide spectrum of machine vision applications including video surveillance, autonomous…
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…