collaborators

6 papers

cs.CV2025

Exploring the correlation between the type of music and the emotions evoked: A study using subjective questionnaires and EEG

Jelizaveta Jankowska, Bożena Kostek, Fernando Alonso-Fernandez +1

The subject of this work is to check how different types of music affect human emotions. While listening to music, a subjective survey and brain activity measurements were carried…

cs.CV2025

Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models

Jiaxiang Liu, Jiawei Du, Xiao Liu +2

Pre-trained vision-language models (VLMs) such as CLIP have demonstrated strong zero-shot capabilities across diverse domains, yet remain highly vulnerable to adversarial perturbat…

cs.CV2025

Overtake Detection in Trucks Using CAN Bus Signals: A Comparative Study of Machine Learning Methods

Fernando Alonso-Fernandez, Talha Hanif Butt, Prayag Tiwari

Safe overtaking manoeuvres in trucks are vital for preventing accidents and ensuring efficient traffic flow. Accurate prediction of such manoeuvres is essential for Advanced Driver…

cs.CV2025

Deep Network Pruning: A Comparative Study on CNNs in Face Recognition

Fernando Alonso-Fernandez, Kevin Hernandez-Diaz, Jose Maria Buades Rubio +2

The widespread use of mobile devices for all kinds of transactions makes necessary reliable and real-time identity authentication, leading to the adoption of face recognition (FR)…

cs.CL2024

FinTeamExperts: Role Specialized MOEs For Financial Analysis

Yue Yu, Prayag Tiwari

Large Language Models (LLMs), such as ChatGPT, Phi3 and Llama-3, are leading a significant leap in AI, as they can generalize knowledge from their training to new tasks without fin…

cs.CV2024

Combined CNN and ViT features off-the-shelf: Another astounding baseline for recognition

Fernando Alonso-Fernandez, Kevin Hernandez-Diaz, Prayag Tiwari +1

We apply pre-trained architectures, originally developed for the ImageNet Large Scale Visual Recognition Challenge, for periocular recognition. These architectures have demonstrate…