activity
20242026
most citedSolving nonograms using Neural Networks

4 citations · 7 across the 3 of their papers we have counts for

collaborators

7 papers

cs.HC2026

Evaluating multimodal emotion recognition in proactive conversational agents: A user study

Adnana Dragut, Raquel Lacuesta, F. Xavier Gaya-Morey +1

This article presents a multimodal emotion recognition module integrated into a proactive Socially Interactive Agent (SIA) powered by generative artificial intelligence. The system…

cs.AI20254 cited

Solving nonograms using Neural Networks

José María Buades Rubio, Antoni Jaume-i-Capó, David López González +1

Nonograms are logic puzzles in which cells in a grid must be colored or left blank according to the numbers that are located in its headers. In this study, we analyze different tec…

cs.CV20243 cited

Automated facial recognition system using deep learning for pain assessment in adults with cerebral palsy

Álvaro Sabater-Gárriz, F. Xavier Gaya-Morey, José María Buades-Rubio +3

Background: Pain assessment in individuals with neurological conditions, especially those with limited self-report ability and altered facial expressions, presents challenges. Exis…

cs.CV2024

Assessing the Efficacy of Deep Learning Approaches for Facial Expression Recognition in Individuals with Intellectual Disabilities

F. Xavier Gaya-Morey, Silvia Ramis, Jose M. Buades-Rubio +1

Facial expression recognition has gained significance as a means of imparting social robots with the capacity to discern the emotional states of users. The use of social robotics i…

cs.CV2024

Unveiling the Human-like Similarities of Automatic Facial Expression Recognition: An Empirical Exploration through Explainable AI

F. Xavier Gaya-Morey, Silvia Ramis-Guarinos, Cristina Manresa-Yee +1

Facial expression recognition is vital for human behavior analysis, and deep learning has enabled models that can outperform humans. However, it is unclear how closely they mimic h…

cs.CV2024

REVEX: A Unified Framework for Removal-Based Explainable Artificial Intelligence in Video

F. Xavier Gaya-Morey, Jose M. Buades-Rubio, I. Scott MacKenzie +1

We developed REVEX, a removal-based video explanations framework. This work extends fine-grained explanation frameworks for computer vision data and adapts six existing techniques…