421 a 430 de 940 Resultados
4 ago 2023 - EMPATIA-CM (protEcción integral de las víctimas de violencia de género Mediante comPutación AfecTIva multimodAl)
Miranda Calero, José Angel; Gutiérrez Martín, Laura; Martínez Rubio, Eva; Blanco Ruiz, María Ángeles; Sainz de Baranda Andújar, Clara; Romero Perales, Elena; San Segundo Manuel, Rosa; López Ongil, Celia, 2022, "UC3M4Safety Database - WEMAC: Biopsychosocial questionnaire and informed consent", https://doi.org/10.21950/U5DXJR, e-cienciaDatos, V3
EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detectio... |
4 ago 2023 - EMPATIA-CM (protEcción integral de las víctimas de violencia de género Mediante comPutación AfecTIva multimodAl)
Miranda Calero, José Angel; Gutiérrez Martín, Laura; Martínez Rubio, Eva; Blanco Ruiz, María Ángeles; Sainz de Baranda Andújar, Clara; Romero Perales, Elena; Alboreca Fernández-Barredo, Bárbara; San Segundo Manuel, Rosa; López Ongil, Celia, 2022, "UC3M4Safety Database - WEMAC: Emotional labelling", https://doi.org/10.21950/RYUCLV, e-cienciaDatos, V3
EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detectio... |
4 ago 2023 - EMPATIA-CM (protEcción integral de las víctimas de violencia de género Mediante comPutación AfecTIva multimodAl)
Miranda Calero, José Angel; Gutiérrez Martín, Laura; Canabal Benito, Manuel Felipe; Paez Montoro, Alba; Ramírez Bárcenas, Alberto; Lanza Gutiérrez, José Manuel; Romero Perales, Elena; López Ongil, Celia, 2022, "UC3M4Safety Database - WEMAC: Physiological signals", https://doi.org/10.21950/FNUHKE, e-cienciaDatos, V3
EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detectio... |
4 ago 2023 - EMPATIA-CM (protEcción integral de las víctimas de violencia de género Mediante comPutación AfecTIva multimodAl)
Rituerto González, Esther; Miranda Calero, José Angel; Luis Mingueza, Clara; Gutiérrez Martín, Laura; Canabal Benito, Manuel Felipe; Lanza Gutiérrez, José Manuel; Peláez Moreno, Carmen; López Ongil, Celia, 2022, "UC3M4Safety Database - WEMAC: Audio features", https://doi.org/10.21950/XKHCCW, e-cienciaDatos, V4
EMPATIA-CM (Comprehensive Protection of Gender-based Violence Victims through Multimodal Affective Computing) is a research project that aims to generally understand the reactions of Gender-based Violence Victims to situations of danger, generate mechanisms for automatic detectio... |
3 ago 2023
de-la-Torre Cañizares, Rubén; Jardón Huete, Alberto; Oña Simbaña, Edwin; González Victores, Juan, 2023, "Synthetic patients with .trc movements", https://doi.org/10.21950/CWZNVC, e-cienciaDatos, V2
This dataset contains 92 heterogeneous Blender models with different height, mass, weight, bone length or muscular tone. Furthermore, 4 movements such as: Shoulder Flexion-Extension, Shoulder Abduction-Adduction, Elbow Flexion-Extension and Forearm Supination-Pronation are added... |
28 jul 2023 - Federico-Tena World Population Historical Database
Federico, Giovanni; Tena Junguito, Antonio, 2023, "Federico-Tena World Population Historical Database : Saint Barthélemy (Norwegian colonies)", https://doi.org/10.21950/OGPYF5, e-cienciaDatos, V1
Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Saint Barthélemy (Norwegian colonies) |
27 jul 2023 - Federico-Tena World Population Historical Database
Federico, Giovanni; Tena Junguito, Antonio, 2023, "Federico-Tena World Population Historical Database : Africa", https://doi.org/10.21950/8EWODF, e-cienciaDatos, V1
Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Africa |
26 jul 2023
CHEN, Junwei; DISCETTI, Stefano; RAIOLA, Marco, 2025, "Dataset of "Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes"", https://doi.org/10.5281/ZENODO.6473075
Dataset of the article Pressure from data-driven estimation of velocity fields using snapshot PIV and fast probes (https://doi.org/10.1016/j.expthermflusci.2022.110647). A data-driven method is applied to combine non-time-resolved velocity field and fast probe data, and achieve t...Dataset recolectado desde Zenodo con autores de la UC3M. El enlace le llevará directamente a los datos originales en dicho archivo. |
26 jul 2023
Tirelli, Iacopo; Ianiro, Andrea; Discetti, Stefano, 2025, "Dataset of "An end-to-end KNN-based PTV approach for high-resolution measurements and uncertainty quantification"", https://doi.org/10.5281/ZENODO.6922577
Dataset of the article "An end-to-end KNN-based PTV approach for high-resolution measurements and uncertainty quantification" (https://doi.org/10.1016/j.expthermflusci.2022.110756). Local similarity between non-time-resolved snapshots is enforced by KNN to extract high-resolution...Dataset recolectado desde Zenodo con autores de la UC3M. El enlace le llevará directamente a los datos originales en dicho archivo. |
26 jul 2023
Güemes, Alejandro; Sanmiguel Vila, Carlos; Discetti, Stefano, 2025, "Dataset of "Super-resolution generative adversarial networks of randomly seeded fields"", https://doi.org/10.5281/ZENODO.7191210
Dataset of the article "Super-resolution generative adversarial networks of randomly seeded fields" (https://doi.org/10.1038/s42256-022-00572-7) The codes processing data here are on https://github.com/eaplab/RaSeedGAN This project has received funding from the European Research...Dataset recolectado desde Zenodo con autores de la UC3M. El enlace le llevará directamente a los datos originales en dicho archivo. |