64 citations · 140 across the 10 of their papers we have counts for
11 papers
Extended Weighted ABG: A Robust Non-Linear ABG-Based Approach for Optimal Combination of ABG Path-Loss Propagation Models
David. Casillas-Pérez, Daniel. Merino-Pérez, Silvia. Jiménez-Fernández +2
This paper proposes a robust non-linear generalized path-loss propagation model, the Extended Weighted ABG (EWABG), which efficiently allows generating a path-loss propagation mode…
A multi-algorithm approach for operational human resources workload balancing in a last mile urban delivery system
Luis M. Moreno-Saavedra, Silvia Jimenez-Fernandez, Antonio Portilla-Figueras +2
Efficient workload assignment to the workforce is critical in last-mile package delivery systems. In this context, traditional methods of assigning package deliveries to workers ba…
CoSeNet: A Novel Approach for Optimal Segmentation of Correlation Matrices
Alberto. Palomo-Alonso, David Casillas-Perez, Silvia Jimenez-Fernandez +2
In this paper, we propose a novel approach for the optimal identification of correlated segments in noisy correlation matrices. The proposed model is known as CoSeNet (Correlation…
Inertial Sensors for Human Motion Analysis: A Comprehensive Review
Sara García-de-Villa, David Casillas-Pérez, Ana Jiménez-Martín +1
Inertial motion analysis is having a growing interest during the last decades due to its advantages over classical optical systems. The technological solution based on inertial mea…
Simultaneous exercise recognition and evaluation in prescribed routines: Approach to virtual coaches
Sara García-de-Villa, David Casillas-Pérez, Ana Jiménez-Martín +1
Home-based physical therapies are effective if the prescribed exercises are correctly executed and patients adhere to these routines. This is specially important for older adults w…
Randomization-based Machine Learning in Renewable Energy Prediction Problems: Critical Literature Review, New Results and Perspectives
Javier Del Ser, David Casillas-Perez, Laura Cornejo-Bueno +4
Randomization-based Machine Learning methods for prediction are currently a hot topic in Artificial Intelligence, due to their excellent performance in many prediction problems, wi…
Towards Dense People Detection with Deep Learning and Depth images
David Fuentes-Jimenez, Cristina Losada-Gutierrez, David Casillas-Perez +4
This paper proposes a DNN-based system that detects multiple people from a single depth image. Our neural network processes a depth image and outputs a likelihood map in image coor…
3DFCNN: Real-Time Action Recognition using 3D Deep Neural Networks with Raw Depth Information
Adrian Sanchez-Caballero, Sergio de López-Diz, David Fuentes-Jimenez +4
Human actions recognition is a fundamental task in artificial vision, that has earned a great importance in recent years due to its multiple applications in different areas. %, suc…
DPDnet: A Robust People Detector using Deep Learning with an Overhead Depth Camera
David Fuentes-Jimenez, Roberto Martin-Lopez, Cristina Losada-Gutierrez +4
In this paper we propose a method based on deep learning that detects multiple people from a single overhead depth image with high reliability. Our neural network, called DPDnet, i…
Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image
David Fuentes-Jimenez, David Casillas-Perez, Daniel Pizarro +2
We present Deep Shape-from-Template (DeepSfT), a novel Deep Neural Network (DNN) method for solving real-time automatic registration and 3D reconstruction of a deformable object vi…
Solutions of Quadratic First-Order ODEs applied to Computer Vision Problems
David Casillas-Perez, Daniel Pizarro, Manuel Mazo +1
This article is a study about the existence and the uniqueness of solutions of a specific quadratic first-order ODE that frequently appears in multiple reconstruction problems. It…