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ORCIDFrancisco López de la Rosa
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2020 – today
- 2024
[j8]José Luis Gómez-Sirvent, Desirée Fernández-Sotos, Francisco López de la Rosa, Antonio Fernández-Caballero:
Building information modeling and affective occupancy evaluation: A scoping review. J. Ambient Intell. Smart Environ. 16(2): 155-166 (2024)- [c6]Francisco López de la Rosa, Lucía Moreno-Salvador, José Luis Gómez-Sirvent, Rafael Morales, Roberto Sánchez-Reolid, Antonio Fernández-Caballero:
Improved Surface Defect Classification from a Simple Convolutional Neural Network by Image Preprocessing and Data Augmentation. IWINAC (2) 2024: 23-32 - 2023
- [j7]Francisco López de la Rosa
, José Luis Gómez-Sirvent, Rafael Morales, Roberto Sánchez-Reolid, Antonio Fernández-Caballero:
Defect detection and classification on semiconductor wafers using two-stage geometric transformation-based data augmentation and SqueezeNet lightweight convolutional neural network. Comput. Ind. Eng. 183: 109549 (2023) - [j6]Lidia M. Belmonte, Eva Segura, Francisco López de la Rosa, José Luis Gómez-Sirvent, Antonio Fernández-Caballero, Rafael Morales:
Training industrial engineers in Logistics 4.0. Comput. Ind. Eng. 184: 109550 (2023) - [c5]José Luis Gómez-Sirvent, Desirée Fernández-Sotos, Francisco López de la Rosa, Alicia Fernández-Sotos, Antonio Fernández-Caballero:
VRPrOE Toolbox for Virtual Pre-occupancy Evaluation: Proof of Concept on a BIM Model of a Conservatory Classroom. ISAmI 2023: 189-198 - [c4]Luis Zhinin-Vera, Jonathan Zhiminaicela-Cabrera, Elena Pretel, Pamela Suárez, Oscar Chang, Francesc Anton Castro, Francisco López de la Rosa:
Artificial Vision Technique to Detect and Classify Cocoa Beans. IWANN (2) 2023: 217-228 - [c3]Francisco López de la Rosa, José Luis Gómez-Sirvent, Lidia M. Belmonte, Rafael Morales, Antonio Fernández-Caballero:
Fine-Tuned SqueezeNet Lightweight Model for Classifying Surface Defects in Hot-Rolled Steel. IWANN (1) 2023: 221-233 - 2022
- [j5]Francisco López de la Rosa, José Luis Gómez-Sirvent, Rafael Morales, Roberto Sánchez-Reolid, Antonio Fernández-Caballero:
A deep residual neural network for semiconductor defect classification in imbalanced scanning electron microscope datasets. Appl. Soft Comput. 131: 109743 (2022) - [j4]Roberto Sánchez-Reolid, Francisco López de la Rosa, María T. López, Antonio Fernández-Caballero:
One-dimensional convolutional neural networks for low/high arousal classification from electrodermal activity. Biomed. Signal Process. Control. 71(Part): 103203 (2022) - [j3]Francisco López de la Rosa, José Luis Gómez-Sirvent, Roberto Sánchez-Reolid, Rafael Morales, Antonio Fernández-Caballero:
Geometric transformation-based data augmentation on defect classification of segmented images of semiconductor materials using a ResNet50 convolutional neural network. Expert Syst. Appl. 206: 117731 (2022) - [j2]Roberto Sánchez-Reolid, Francisco López de la Rosa, Daniel Sánchez-Reolid, María T. López, Antonio Fernández-Caballero:
Machine Learning Techniques for Arousal Classification from Electrodermal Activity: A Systematic Review. Sensors 22(22): 8886 (2022) - [c2]Francisco López de la Rosa, José Luis Gómez-Sirvent, Corinna Kofler, Rafael Morales, Antonio Fernández-Caballero:
Detection of Unknown Defects in Semiconductor Materials from a Hybrid Deep and Machine Learning Approach. IWINAC (1) 2022: 356-365 - 2021
- [j1]Lidia M. Belmonte, Arturo S. García, Rafael Morales, Jose Luis de la Vara, Francisco López de la Rosa, Antonio Fernández-Caballero:
Feeling of Safety and Comfort towards a Socially Assistive Unmanned Aerial Vehicle That Monitors People in a Virtual Home. Sensors 21(3): 908 (2021) - [c1]Roberto Sánchez-Reolid, Francisco López de la Rosa, Daniel Sánchez-Reolid, María T. López, Antonio Fernández-Caballero:
Feature and Time Series Extraction in Artificial Neural Networks for Arousal Detection from Electrodermal Activity. IWANN (1) 2021: 265-276
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