129 citations · 168 across the 14 of their papers we have counts for
14 papers
Dynamic Dropout: Leveraging Conway's Game of Life for Neural Networks Regularization
David Freire-Obregón, José Salas-Cáceres, Modesto Castrillón-Santana
Regularization techniques play a crucial role in preventing overfitting and improving the generalization performance of neural networks. Dropout, a widely used regularization techn…
Modeling Cultural Bias in Facial Expression Recognition with Adaptive Agents
David Freire-Obregón, José Salas-Cáceres, Javier Lorenzo-Navarro +3
Facial expression recognition (FER) must remain robust under both cultural variation and perceptually degraded visual conditions, yet most existing evaluations assume homogeneous d…
Mapping Emotions in the Brain: A Bi-Hemispheric Neural Model with Explainable Deep Learning
David Freire-Obregón, Agnieszka Dubiel, Prasoon Kumar Vinodkumar +3
Recent advances have shown promise in emotion recognition from electroencephalogram (EEG) signals by employing bi-hemispheric neural architectures that incorporate neuroscientific…
Predicting Soccer Penalty Kick Direction Using Human Action Recognition
David Freire-Obregón, Oliverio J. Santana, Javier Lorenzo-Navarro +2
Action anticipation has become a prominent topic in Human Action Recognition (HAR). However, its application to real-world sports scenarios remains limited by the availability of s…
An Evaluation of a Visual Question Answering Strategy for Zero-shot Facial Expression Recognition in Still Images
Modesto Castrillón-Santana, Oliverio J Santana, David Freire-Obregón +2
Facial expression recognition (FER) is a key research area in computer vision and human-computer interaction. Despite recent advances in deep learning, challenges persist, especial…
Transfer Learning from Simulated to Real Scenes for Monocular 3D Object Detection
Sondos Mohamed, Walter Zimmer, Ross Greer +6
Accurately detecting 3D objects from monocular images in dynamic roadside scenarios remains a challenging problem due to varying camera perspectives and unpredictable scene conditi…
Towards Bi-Hemispheric Emotion Mapping through EEG: A Dual-Stream Neural Network Approach
David Freire-Obregón, Daniel Hernández-Sosa, Oliverio J. Santana +2
Emotion classification through EEG signals plays a significant role in psychology, neuroscience, and human-computer interaction. This paper addresses the challenge of mapping human…
A Large-Scale Re-identification Analysis in Sporting Scenarios: the Betrayal of Reaching a Critical Point
David Freire-Obregón, Javier Lorenzo-Navarro, Oliverio J. Santana +2
Re-identifying participants in ultra-distance running competitions can be daunting due to the extensive distances and constantly changing terrain. To overcome these challenges, com…
An X3D Neural Network Analysis for Runner's Performance Assessment in a Wild Sporting Environment
David Freire-Obregón, Javier Lorenzo-Navarro, Oliverio J. Santana +2
We present a transfer learning analysis on a sporting environment of the expanded 3D (X3D) neural networks. Inspired by action quality assessment methods in the literature, our met…
Towards cumulative race time regression in sports: I3D ConvNet transfer learning in ultra-distance running events
David Freire-Obregón, Javier Lorenzo-Navarro, Oliverio J. Santana +2
Predicting an athlete's performance based on short footage is highly challenging. Performance prediction requires high domain knowledge and enough evidence to infer an appropriate…
Decontextualized I3D ConvNet for ultra-distance runners performance analysis at a glance
David Freire-Obregón, Javier Lorenzo-Navarro, Modesto Castrillón-Santana
In May 2021, the site runnersworld.com published that participation in ultra-distance races has increased by 1,676% in the last 23 years. Moreover, nearly 41% of those runners part…
Deep learning for source camera identification on mobile devices
David Freire-Obregón, Fabio Narducci, Silvio Barra +1
In the present paper, we propose a source camera identification method for mobile devices based on deep learning. Recently, convolutional neural networks (CNNs) have shown a remark…
Comparative study of histogram distance measures for re-identification
Pedro A. Marín-Reyes, Javier Lorenzo-Navarro, Modesto Castrillón-Santana
Color based re-identification methods usually rely on a distance function to measure the similarity between individuals. In this paper we study the behavior of several histogram di…
Optimized clothes segmentation to boost gender classification in unconstrained scenarios
D. Freire-Obregón, M. Castrillón-Santana, J. Lorenzo-Navarro
Several applications require demographic information of ordinary people in unconstrained scenarios. This is not a trivial task due to significant human appearance variations. In th…