1 citations · 1 across the 7 of their papers we have counts for
7 papers
Mind2Drive: Predicting Driver Intentions from EEG in Real-world On-Road Driving
Ghadah Alosaimi, Hanadi Alhamdan, Wenke E +3
Predicting driver intention from neurophysiological signals offers a promising pathway for enhancing proactive safety in advanced driver assistance systems, yet remains challenging…
EEG-Driven Intention Decoding: Offline Deep Learning Benchmarking on a Robotic Rover
Ghadah Alosaimi, Maha Alsayyari, Yixin Sun +3
Brain-computer interfaces (BCIs) provide a hands-free control modality for mobile robotics, yet decoding user intent during real-world navigation remains challenging. This work pre…
SKDU at De-Factify 4.0: Natural Language Features for AI-Generated Text-Detection
Shrikant Malviya, Pablo Arnau-González, Miguel Arevalillo-Herráez +1
The rapid advancement of large language models (LLMs) has introduced new challenges in distinguishing human-written text from AI-generated content. In this work, we explored a pipe…
BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction
Ruochen Li, Stamos Katsigiannis, Tae-Kyun Kim +1
Trajectory prediction allows better decision-making in applications of autonomous vehicles or surveillance by predicting the short-term future movement of traffic agents. It is cla…
Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction
Ruochen Li, Tanqiu Qiao, Stamos Katsigiannis +2
Pedestrian trajectory prediction aims to forecast future movements based on historical paths. Spatial-temporal (ST) methods often separately model spatial interactions among pedest…
On Bias and Fairness in NLP: Investigating the Impact of Bias and Debiasing in Language Models on the Fairness of Toxicity Detection
Fatma Elsafoury, Stamos Katsigiannis
Language models are the new state-of-the-art natural language processing (NLP) models and they are being increasingly used in many NLP tasks. Even though there is evidence that lan…