65 citations · 287 across the 27 of their papers we have counts for
6 papers · 1 filter
Deep Residual Networks for Gravitational Wave Detection
Paraskevi Nousi, Alexandra E. Koloniari, Nikolaos Passalis +3
Traditionally, gravitational waves are detected with techniques such as matched filtering or unmodeled searches based on wavelets. However, in the case of generic black hole binari…
A Novel Dataset for Evaluating and Alleviating Domain Shift for Human Detection in Agricultural Fields
Paraskevi Nousi, Emmanouil Mpampis, Nikolaos Passalis +2
In this paper we evaluate the impact of domain shift on human detection models trained on well known object detection datasets when deployed on data outside the distribution of the…
MLGWSC-1: The first Machine Learning Gravitational-Wave Search Mock Data Challenge
Marlin B. Schäfer, Ondřej Zelenka, Alexander H. Nitz +20
We present the results of the first Machine Learning Gravitational-Wave Search Mock Data Challenge (MLGWSC-1). For this challenge, participating groups had to identify gravitationa…
VPIT: Real-time Embedded Single Object 3D Tracking Using Voxel Pseudo Images
Illia Oleksiienko, Paraskevi Nousi, Nikolaos Passalis +2
In this paper, we propose a novel voxel-based 3D single object tracking (3D SOT) method called Voxel Pseudo Image Tracking (VPIT). VPIT is the first method that uses voxel pseudo i…
Deep Residual Error and Bag-of-Tricks Learning for Gravitational Wave Surrogate Modeling
Styliani-Christina Fragkouli, Paraskevi Nousi, Nikolaos Passalis +3
Deep learning methods have been employed in gravitational-wave astronomy to accelerate the construction of surrogate waveforms for the inspiral of spin-aligned black hole binaries,…
OpenDR: An Open Toolkit for Enabling High Performance, Low Footprint Deep Learning for Robotics
N. Passalis, S. Pedrazzi, R. Babuska +15
Existing Deep Learning (DL) frameworks typically do not provide ready-to-use solutions for robotics, where very specific learning, reasoning, and embodiment problems exist. Their r…