@article{nokey,

title = {Exploring the implementation of the pepper social robot in formal education: a scoping review},

author = {Rosabel Martínez-Roig and María Aragones Gonzalez and Miguel Cazorla},

year  = {2026},

date = {2026-07-11},

journal = {Journal of new approaches for educational research},

volume = {15},

number = {22},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {FAKES FOR ALL: A Demographically Inclusive Face-Swapped Video Dataset for Fair Deepfake Detection},

author = {Monica Pina and Francisco Gomez-Donoso and Miguel Cazorla},

year  = {2026},

date = {2026-07-07},

journal = {IEEE Acess},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Older adults’ initial perceptions of a quadruped robot during assisted walks in residential care: A qualitative pilot study  },

author = {Veronica Onrubia and Rosabel Martínez and Carlos Zambrana and Miguel Cazorla},

year  = {2026},

date = {2026-07-03},

journal = {Computers in Human Behavior Reports},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {PIO, A Large-Scale Dataset for Broiler Chicken Detection under Real Poultry Farming Conditions,},

author = {Keyla Boniche and Edmanuel Cruz and José Carlos Rangel and Miguel Hidalgo-Rodríguez and Francisco Gomez-Donoso},

year  = {2026},

date = {2026-06-10},

journal = {Scientific Data},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Multimodal Classification of Keratoconus Progression Using Corneal Surface Geometry and Refractive Data: The Role of Peripheral Regions and Missing-Data Patterns},

author = {Carlos Cano-Espinosa and Jose González and Carmelo Gómez and josé Miguel Bolarín and Jorge Alió del Barrio and Francisco Cavas},

doi = {10.1016/j.knosys.2026.116402},

year  = {2026},

date = {2026-06-10},

journal = {Knowledge-Based Systems},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Simulating Students with Large Language Models: A Review of Architecture, Mechanisms, and Role Modelling in Education with Generative AI},

author = {Luis Marquez-Carpintero and Alberto Lopez-Sellers and Miguel Cazorla},

year  = {2026},

date = {2026-05-30},

urldate = {2026-05-30},

journal = {Computer Science Review},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {AIDEN: Design and Pilot Study of an AI Assistant for the Visually Impaired},

author = {Luis Marquez-Carpintero and Francisco Gomez-Donoso and Zuria Bauer and Bessie Dominguez-Dager and Álvaro Belmonte-Baeza and Mónica Pina and Francisco Morillas-Espejo and Felix Escalona and Miguel Cazorla},

year  = {2026},

date = {2026-05-14},

journal = {IEEE Access},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Multimodal Recognition of Out-of-Distribution Individuals Using Contrastive Learning},

author = {Sergio García and Francisco Gomez-Donoso and Miguel Cazorla},

url = {https://www.mdpi.com/2673-2688/7/5/162},

doi = {https://doi.org/10.3390/ai7050162},

issn = {2673-2688},

year  = {2026},

date = {2026-05-06},

urldate = {2026-04-24},

journal = {AI},

volume = {7},

issue = {5},

abstract = {This paper presents an innovative methodology detecting out-of-distribution individuals based on a multimodal contrastive learning approach. The system combines voice and facial image data by projecting them into a shared representation in the embedding space, enable accurate identification of previously unseen individuals. This approach overcomes the limitations of traditional methods by providing more robust and consistent detection in dynamic scenarios, using advanced neural networks and optimized contrastive losses. Specifically, the main contribution of this work is the introduction of a multimodal contrastive framework that performs cross-modal consistency verification between facial and vocal representations, enabling reliable detection of out-of-distribution individuals without the need for identity gallery retrieval. Experimental results on multiple datasets highlight the effectiveness of the system, with accuracy above 90% in detecting in-distribution samples in all evaluated cases. Regarding the identification of out-of-distribution cases, the system maintains outstanding performance, achieving values close to 90% on average, with some datasets exceeding 95%. These results underscore its ability to recognize both known identities and handle unknown data, even under challenging conditions. This approach represents a significant advancement in the multimodal recognition of individuals, with potential applications in critical areas such as security, surveillance, and human–computer interaction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Effectiveness of virtual reality interventions for enhancing assertiveness and conflict resolution in adolescents and young adults with autism spectrum disorder: a scoping review},

author = {Alejandro Sanchez-Ronco and Rosabel Roig-Vila and Miguel Cazorla},

year  = {2026},

date = {2026-05-04},

journal = {Review Journal of Autism and Developmental Disorders},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {When Customer Support Becomes an Attack Surface. How Support Workflows Act as Shadow APIs to Bypass Authentication},

author = {Luis Marquez-Carpintero and Ernesto Canales and Miguel Cazorla },

year  = {2026},

date = {2026-04-14},

journal = {IEEE Security & Privacy},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {MR. CHEQA: Mixed Reality for Construction House Evaluation and Quality Assessing },

author = {David Martinez-Miranzo and Carlos Rizo-Maestre and Francisco Gomez-Donoso and Miguel Cazorla 



},

doi = {10.1061/JCEMD4/COENG-18883},

year  = {2026},

date = {2026-04-10},

journal = {Journal of Construction Engineering and Management},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Predicting public Intensive care unit mortality and hospitalization using Data: An evaluation of Brazil’s Largest COVID-19 epidemiological dataset},

author = {Lia da Graça and João Paulo de Oliveira and Aratã Saraiva and Richarlisson Borges de Morais and Monica Taminato and Hugo Fernandes and German Gonzalez-Serrano},

doi = {https://doi.org/10.1016/j.iccn.2026.104363},

year  = {2026},

date = {2026-04-07},

journal = {Intensive and critical care nursing},

volume = {95},

pages = {104363},

abstract = {Objectives

To assess the SRAG dataset’s potential for modeling COVID-19 mortality and LOS-ICU, identify key data gaps, and support the development of predictive tools for ICU planning in future outbreaks.

Methods

The SRAG dataset was split into training and test sets, followed by a hybrid feature variable selection strategy, which applied the XGBoost classifier and subsequent inclusion of comorbidities. Mortality prediction employed six supervised learning algorithms, while LOS-ICU was modeled using five regression techniques. Evaluation metrics included Receiver Operating Characteristic (ROC) curves, F1-score, sensitivity, precision, and specificity for mortality classification; and Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2 for LOS-ICU. Models were tuned to address data imbalance and improve generalizability across the dataset.

Results

A total of 365,572 ICU inpatients were analyzed. Predictive models estimated mortality at around 51%, compared to an actual observed rate of ∼ 54%, with good discriminatory ability (AUC between 0.73 and 0.85). The average ICU stay was 11.6 days. Boosting models achieved the best performance for mortality prediction, with XGBoost reaching AUC = 0.85 and F1-score = 0.80, supporting early identification of high-risk patients. LOS-ICU regressions yielded MAE = 4–6 days and R2 = 0.35–0.37, indicating a predicted ICU stay of 11.6 ± 6 days and reflecting limited explanatory power due to missing clinical biomarkers. Mortality predictions were robust for triage support, while ICU stay estimates, though less precise, remain useful for operational planning.

Conclusions

This research pioneered the use of a large-scale, highly granular public dataset and leveraged it for mortality prediction in COVID-19 patients in public ICUs. Given the unprecedented scale, academic and managerial improvements were brought to the field, offering generalizable solutions to support ICU triage and early warnings during outbreaks. Addressing the gaps of SRAG could enhance its utility for predictive modeling, especially in LOS-ICU modeling, enabling more accurate results.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Path Planning and Reinforcement Learning-Driven Control of On-Orbit Free-Flying Multi-Arm Robots},

author = {Álvaro Belmonte-Baeza and José Luis Ramón and Leonard Felicetti and Miguel Cazorla and Jorge Pomares},

year  = {2026},

date = {2026-03-23},

urldate = {2026-03-23},

journal = {International Journal of Robotics Resarch},

volume = {Accepted},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {The Convergence of Artificial Intelligence in Measuring Attention and Emotion in Digital Technology-Enhanced Tertiary Education: A Scoping Review},

author = {Javier Arranz Romero and Rosabel Roig-Vila and Miguel Cazorla},

doi = {https://doi.org/10.3390/educsci16030433},

year  = {2026},

date = {2026-03-10},

urldate = {2026-03-10},

journal = {Education Sciences},

volume = {16},

number = {3},

pages = {433},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = { IPA 2.0: Validation of an Interpretable Emotion-Attention Index for Neuroadaptive Learning with AI in Real Environments},

author = {Javier Arranz-Romero and Rosabel Roig-Vila and Miguel Cazorla},

url = {https://www.mdpi.com/2076-3417/16/5/2515},

doi = {https://doi.org/10.3390/app16052515},

year  = {2026},

date = {2026-03-03},

urldate = {2026-03-03},

journal = {Applied Sciences},

volume = {16},

number = {5},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Escaping the big data paradigm in self-supervised representation learning. },

author = {Carlos Vélez-García and Miguel Cazorla and Jorge Pomares},

url = {https://www.sciencedirect.com/science/article/pii/S1077314226000652},

doi = {https://doi.org/10.1016/j.cviu.2026.104698},

issn = {1077-3142},

year  = {2026},

date = {2026-02-06},

urldate = {2026-02-06},

journal = {Computer vision and image understanding},

volume = {266},

pages = {104698},

abstract = {The reliance on large-scale datasets and extensive computational resources has become a significant barrier to advancing representation learning from images, particularly in domains where data is scarce or expensive to obtain. In this paper, we address the critical question: Can we escape the big data paradigm in self-supervised representation learning from images? We introduce SCOTT (Sparse Convolutional Tokenizer for Transformers), a shallow tokenization architecture that is compatible with Masked Image Modeling (MIM) tasks. SCOTT injects convolutional inductive biases into Vision Transformers (ViTs), enhancing their efficacy in small-scale data regimens. Alongside, we propose to train on a Joint-Embedding Predictive Architecture within a MIM framework (MIM-JEPA), operating in latent representation space to capture more semantic features. Our approach enables ViTs to be trained from scratch on datasets orders of magnitude smaller than traditionally required — without relying on massive external datasets for pretraining. We validate our method on three small-size, standard-resolution, fine-grained datasets: Oxford Flowers-102, Oxford IIIT Pets-37, and ImageNet-100. Despite the challenges of limited data and high intra-class similarity of these datasets, our frozen SCOTT models pretrained with MIM-JEPA significantly outperform fully supervised methods and achieve competitive results with state-of-the-art approaches that rely on large-scale pretraining, complex image augmentations and bigger model sizes. By demonstrating that robust off-the-shelf representations can be learned with limited data, compute, and model sizes, our work paves the way for computer applications in resource constrained environments such as medical imaging or robotics.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {Improving face re-identification via identity-conditioned synthetic augmentation and inference-time embedding fusion},

author = {Hector Penades and Felix Escalona and Miguel Cazorla},

url = {https://www.sciencedirect.com/science/article/pii/S0957417426002150},

doi = {https://doi.org/10.1016/j.eswa.2026.131302},

issn = {1873-6793},

year  = {2026},

date = {2026-01-22},

urldate = {2026-01-22},

journal = {Expert systems With Applications},

volume = {310},

pages = {131302},

abstract = {The task of face re-identification seeks to match identities across images captured under varying conditions. In conventional single-registration scenarios, only one real image per subject is available during inference, limiting the discriminative capability of the embedding. Advances in synthetic data present new opportunities for improving recognition systems, particularly as privacy concerns restrict data availability. We propose a novel method that leverages identity-guided synthetic augmentation to enrich facial representations at inference time. Unlike traditional data augmentation, it enhances embeddings through sample aggregation, introducing an inference-time paradigm for representation enrichment without expanding the training set or retraining existing models. Using Arc2Face, we generate diverse, identity-consistent synthetic images from each real sample, synthesizing multiple facial variations to approximate the distributional space around each identity. A non-parametric analysis of ten embedding fusion strategies showed consistent improvements over the baselines, with the Mean, Median, and hybrid Mean-Median (Meta-MM) achieving the best performance and Meta-MM showing the lowest variability across models. Experiments demonstrated consistent improvements across re-identification and verification settings. On Labeled Faces in the Wild (LFW) dataset, Rank-1 accuracy improved by an average of 6.97 points and mean Average Precision (mAP) by 5.82 and 8.10 points. On the Surveillance Cameras Face (SCFace) dataset, a low-quality, cross-distance dataset, Rank-1 gains ranged from 10.98 to 31.33 points. On the Cross-Pose LFW (CPLFW) verification benchmark, accuracy generally matched or exceeded AdaFace baselines, with gains of up to 5.57 points. Incorporating latent consistency models with low-rank adaptation (LCM-LoRA) accelerated sample generation tenfold, making the framework suitable for large-scale applications.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = { Artificial intelligence as a tool for bionomic transects: the case of Isidella elongata (Esper, 1788) forests in the Western Mediterranean},

author = {Alejandro Carmona-Rodríguez and Francisco Gomez-Donoso and Miguel Cazorla and Alba Cobo-Viveros and Ricardo Aguilar and Alfonso Ramos-Esplá Elena Guijarro-García },

doi = {https://doi.org/10.1016/j.marenvres.2025.107830},

year  = {2026},

date = {2026-01-10},

urldate = {2026-01-10},

journal = { Marine Environmental Research},

volume = {215},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RizoMaestre2026IntelligentVentilationb,

title = {Intelligent Ventilation and Indoor Air Quality: State of the Art Review (2017–2025)},

author = {Carlos Rizo-Maestre and José María Flores-Moreno and Amor Nebot Sanz and Víctor Echarri-Iribarren},

url = {https://doi.org/10.3390/buildings16010065},

doi = {10.3390/buildings16010065},

year  = {2026},

date = {2026-01-01},

journal = {Buildings},

volume = {16},

number = {1},

pages = {65},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RizoMaestre2026EDGEb,

title = {Methodology for the Rehabilitation and Improvement of Energy Efficiency in Social Housing in a Hot–Humid Climate with the EDGE App: Case Study in Montería, Colombia},

author = {Carlos Rizo-Maestre and Rafael-Andrés Bracamonte-Vega and Carlos Pérez-Carramiñana and Víctor Echarri-Iribarren},

url = {https://doi.org/10.3390/su18010243},

doi = {10.3390/su18010243},

year  = {2026},

date = {2026-01-01},

journal = {Sustainability},

volume = {18},

number = {1},

pages = {243},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RizoMaestre2026MultiAgentb,

title = {Multi-Agent Systems and Digital Twins as a Basis for Smart Buildings with Integrated Sustainable Efficient Ventilation},

author = {Carlos Rizo-Maestre and José María Flores-Moreno and Amor Nebot-Sanz and José Antonio Huesca-Tortosa},

url = {https://doi.org/10.3390/buildings16051026},

doi = {10.3390/buildings16051026},

year  = {2026},

date = {2026-01-01},

journal = {Buildings},

volume = {16},

number = {5},

pages = {1026},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FrancoQuintero2026ReuseBuiltEnvironmentb,

title = {Reuse of Drinking Water in the Built Environment: Types of Conflict, Legitimacy and Governance},

author = {Juan Franco-Quintero and Carlos Rizo-Maestre and María Dolores Andújar-Montoya},

url = {https://doi.org/10.20944/preprints202604.1727.v1},

doi = {10.20944/preprints202604.1727.v1},

year  = {2026},

date = {2026-01-01},

journal = {Preprints},

note = {Preprint, posted 24 April 2026},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CanutMontalva2026TrainingWaterNetworkb,

title = {Design of a Training Water Network Plant for Vocational Education in the Urban Water Cycle: A Case Study in Spain},

author = {Albert Canut-Montalva and Carlos Rizo-Maestre and Joaquín Martínez-López and Joaquín Solbes-Llorca},

url = {https://doi.org/10.3390/su18105075},

doi = {10.3390/su18105075},

year  = {2026},

date = {2026-01-01},

journal = {Sustainability},

volume = {18},

number = {10},

pages = {5075},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FrancoQuintero2026ReuseCitiesb,

title = {Reuse of Drinking Water in the Cities: Types of Conflict, Legitimacy and Governance},

author = {Juan Franco-Quintero and Carlos Rizo-Maestre and María Dolores Andújar-Montoya},

url = {https://doi.org/10.3390/w18121399},

doi = {10.3390/w18121399},

year  = {2026},

date = {2026-01-01},

journal = {Water},

volume = {18},

number = {12},

pages = {1399},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CastilloAlvarez2026BDIb,

title = {Biopolygeneration Diagnostic Index (BDI): An Exergy-Based Framework for Quantifying Maximum Utilization and Thermodynamic Performance in Biomass-Based Bioenergy Plants},

author = {Yoisdel Castillo Alvarez and Reinier Jiménez Borges and Berlan Rodríguez Pérez and Juan Pablo Gómez-Montoya and Carlos Rizo-Maestre and Luis Angel Iturralde Carrera and Juvenal Rodríguez Reséndiz},

url = {https://doi.org/10.3390/environments13060333},

doi = {10.3390/environments13060333},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {Environments},

volume = {13},

number = {6},

pages = {333},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RizoMaestre2026IntelligentVentilation,

title = {Intelligent Ventilation and Indoor Air Quality: State of the Art Review (2017–2025)},

author = {Carlos Rizo-Maestre and José María Flores-Moreno and Amor Nebot Sanz and Víctor Echarri-Iribarren},

url = {https://doi.org/10.3390/buildings16010065},

doi = {10.3390/buildings16010065},

year  = {2026},

date = {2026-01-01},

journal = {Buildings},

volume = {16},

number = {1},

pages = {65},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RizoMaestre2026EDGE,

title = {Methodology for the Rehabilitation and Improvement of Energy Efficiency in Social Housing in a Hot–Humid Climate with the EDGE App: Case Study in Montería, Colombia},

author = {Carlos Rizo-Maestre and Rafael-Andrés Bracamonte-Vega and Carlos Pérez-Carramiñana and Víctor Echarri-Iribarren},

url = {https://doi.org/10.3390/su18010243},

doi = {10.3390/su18010243},

year  = {2026},

date = {2026-01-01},

journal = {Sustainability},

volume = {18},

number = {1},

pages = {243},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{RizoMaestre2026MultiAgent,

title = {Multi-Agent Systems and Digital Twins as a Basis for Smart Buildings with Integrated Sustainable Efficient Ventilation},

author = {Carlos Rizo-Maestre and José María Flores-Moreno and Amor Nebot-Sanz and José Antonio Huesca-Tortosa},

url = {https://doi.org/10.3390/buildings16051026},

doi = {10.3390/buildings16051026},

year  = {2026},

date = {2026-01-01},

journal = {Buildings},

volume = {16},

number = {5},

pages = {1026},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FrancoQuintero2026ReuseBuiltEnvironment,

title = {Reuse of Drinking Water in the Built Environment: Types of Conflict, Legitimacy and Governance},

author = {Juan Franco-Quintero and Carlos Rizo-Maestre and María Dolores Andújar-Montoya},

url = {https://doi.org/10.20944/preprints202604.1727.v1},

doi = {10.20944/preprints202604.1727.v1},

year  = {2026},

date = {2026-01-01},

journal = {Preprints},

note = {Preprint, posted 24 April 2026},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CanutMontalva2026TrainingWaterNetwork,

title = {Design of a Training Water Network Plant for Vocational Education in the Urban Water Cycle: A Case Study in Spain},

author = {Albert Canut-Montalva and Carlos Rizo-Maestre and Joaquín Martínez-López and Joaquín Solbes-Llorca},

url = {https://doi.org/10.3390/su18105075},

doi = {10.3390/su18105075},

year  = {2026},

date = {2026-01-01},

journal = {Sustainability},

volume = {18},

number = {10},

pages = {5075},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{FrancoQuintero2026ReuseCities,

title = {Reuse of Drinking Water in the Cities: Types of Conflict, Legitimacy and Governance},

author = {Juan Franco-Quintero and Carlos Rizo-Maestre and María Dolores Andújar-Montoya},

url = {https://doi.org/10.3390/w18121399},

doi = {10.3390/w18121399},

year  = {2026},

date = {2026-01-01},

journal = {Water},

volume = {18},

number = {12},

pages = {1399},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{CastilloAlvarez2026BDI,

title = {Biopolygeneration Diagnostic Index (BDI): An Exergy-Based Framework for Quantifying Maximum Utilization and Thermodynamic Performance in Biomass-Based Bioenergy Plants},

author = {Yoisdel Castillo Alvarez and Reinier Jiménez Borges and Berlan Rodríguez Pérez and Juan Pablo Gómez-Montoya and Carlos Rizo-Maestre and Luis Angel Iturralde Carrera and Juvenal Rodríguez Reséndiz},

url = {https://doi.org/10.3390/environments13060333},

doi = {10.3390/environments13060333},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {Environments},

volume = {13},

number = {6},

pages = {333},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{marquez2025,

title = {Simulation of Teaching behaviours in Intelligent Tutoring Systems: A Review Using Large Language Models},

author = {Luis Marquez-Carpintero and Alberto Lopez-Sellers and Miguel Cazorla },

doi = {https://doi.org/10.1007/s10462-025-11464-8},

year  = {2025},

date = {2025-12-02},

urldate = {2025-12-02},

journal = {Artificial Intelligence Review},

volume = {59},

number = {56},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rojas2025,

title = {Interactive Digital Twin Workflow for Energy Assessment of Buildings: Integration of Photogrammetry, BIM and Thermography}},

author = {Luis Santiago Rojas-Colmenares and Carlos Rizo-Maestre and Francisco Gómez-Donoso and Pascual Saura-Gómez},

year  = {2025},

date = {2025-11-28},

journal = {Applied Sciences},

volume = {15},

number = {23},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{dominguez2025,

title = {CHIRLA: Comprehensive High-resolution Identification and Re-identification for Large-scale Analysis},

author = {Bessie Dominguez-Dager and Felix Esccalona and Francisco Gomez-Donoso and Miguel Cazorla},

doi = {https://doi.org/10.1038/s41597-025-06425-3},

year  = {2025},

date = {2025-11-25},

urldate = {2025-11-25},

journal = {Scientific Data},

volume = {13},

number = {109},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rizo_Maestre_2025,

title = {Bibliographic Review of Data-Driven Methods for Building Energy Optimisation},

author = {Carlos Rizo-Maestre and Mireia Sempere-Tortosa and Pascual Saura-Hernández and María Dolores Andújar-Montoya},

url = {http://dx.doi.org/10.3390/buildings15213992},

doi = {10.3390/buildings15213992},

issn = {2075-5309},

year  = {2025},

date = {2025-11-01},

journal = {Buildings},

volume = {15},

number = {21},

pages = {3992},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = { Editorial: Methodology for Emotion-Aware Education Based on Artificial Intelligence},

author = {Rosabel Roig-Vila and Miguel Cazorla and Sébastien Lallé},

year  = {2025},

date = {2025-09-16},

journal = { Frontiers in Artificial Intelligence},

keywords = {AI, Education},

pubstate = {published},

tppubtype = {article}

}

@article{Roig-Vila2025,

title = { Implementation of artificial intelligence technologies for the assessment of students' attentional state: a systematic review},

author = {Rosabel Roig-Vila and Paz Prendes-Espinosa and Miguel Cazorla},

doi = {10.3390/app15115990},

year  = {2025},

date = {2025-07-17},

urldate = {2025-07-17},

journal = {Applied Sciences},

volume = {15},

issue = {11},

keywords = {AI, Education},

pubstate = {published},

tppubtype = {article}

}

@article{Marquez-Carpintero2025,

title = {Engineering Young Faculty’s Acceptance of Real-Time behaviour Measurement Software},

author = {Luis Marquez-Carpintero and Francisco Gomez-Donoso and Miguel Cazorla},

doi = {10.3389/fcomp.2025.1565809},

year  = {2025},

date = {2025-07-16},

urldate = {2025-07-16},

journal = {Frontiers in Computer Science},

volume = {7},

keywords = {AI, Education},

pubstate = {published},

tppubtype = {article}

}

@article{Márquez-Carpintero2025b,

title = {Enhancing Engineering and STEM Education with Vision and Multimodal Large Language Models to Predict Student Attention.},

author = {Luis Márquez-Carpintero and Diego Viejo and Miguel Cazorla},

doi = {10.1109/ACCESS.2025.3584025},

year  = {2025},

date = {2025-07-16},

urldate = {2025-07-16},

journal = {IEEE Access},

volume = {13},

keywords = {AI, Education},

pubstate = {published},

tppubtype = {article}

}

@article{sanchez2025,

title = {Slippage detection during manufacturing toy assembly tasks},

author = {Daniel Sánchez-Martínez and Kazuhiro Shimonomura and Juan A. Micó and Carlos A. Jara and Francisco Gomez-Donoso},

doi = {https://doi.org/10.1007/s00170-025-15642-4},

isbn = {1433-3015},

year  = {2025},

date = {2025-05-13},

urldate = {2025-05-13},

journal = {The International Journal of Advanced Manufacturing Technology},

volume = {138},

pages = {2257–2279},

keywords = {},

pubstate = {published},

tppubtype = {article}

}