Zobrazeno 1 - 10
of 953
pro vyhledávání: '"Manuel Gil"'
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-14 (2024)
Abstract This paper presents Multi-view Leap2 Hand Pose Dataset (ML2HP Dataset), a new dataset for hand pose recognition, captured using a multi-view recording setup with two Leap Motion Controller 2 devices. This dataset encompasses a diverse range
Externí odkaz:
https://doaj.org/article/497eecc240ca4da489127fcd9c936510
Autor:
Manuel Gil-Martín, Cristina Luna-Jiménez, Sergio Esteban-Romero, Marcos Estecha-Garitagoitia, Fernando Fernández-Martínez, Luis Fernando D’Haro
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-11 (2024)
Abstract This paper introduces Art_GenEvalGPT, a novel dataset of synthetic dialogues centered on art generated through ChatGPT. Unlike existing datasets focused on conventional art-related tasks, Art_GenEvalGPT delves into nuanced conversations abou
Externí odkaz:
https://doaj.org/article/f5bc4e49571c46e18e22c916fd94966e
Autor:
Rubén Peña-Vélez, Fernando M. Dzul-Pech, Juvenal Salgado-Valencia, Roberto Calva, Manuel Gil-Vargas
Publikováno v:
Boletín Médico del Hospital Infantil de México, Vol 81, Iss 2 (2024)
Introducción: La pancreatitis aguda se observa con mayor frecuencia en la edad pediátrica. Actualmente existen guías de recomendaciones para su adecuado diagnóstico y tratamiento. El objetivo de este estudio fue evaluar el nivel de conocimiento d
Externí odkaz:
https://doaj.org/article/9430acddc5f54e2e9d6ddf5efe97ec96
Publikováno v:
Frontiers in Endocrinology, Vol 15 (2024)
Externí odkaz:
https://doaj.org/article/ecb06786faca43b896e91193e0105143
Publikováno v:
IEEE Access, Vol 11, Pp 137083-137098 (2023)
The clinical environment is one of the most important sources of sensitive patient data in healthcare. These data have attracted cybercriminals who pursue the theft of this information for personal gain. Therefore, protecting these data is a critical
Externí odkaz:
https://doaj.org/article/b5c31459183042b3af0d8ea8dc783c58
Autor:
Ximena Aurora Altonar Gómez, Leobardo Eduardo Contreras Gómez, Manuel Gil Antón, Miguel Ángel Pérez Angón
Publikováno v:
Revista Española de Documentación Científica, Vol 46, Iss 2 (2023)
Este trabajo tiene por objetivo estudiar la relación entre la producción de los documentos indexados del área de ciencias ambientales en la base de datos de SCOPUS y los países mejor evaluados dentro del Índice de Desempeño Ambiental (EPI). Par
Externí odkaz:
https://doaj.org/article/0de44186eb224e0da55092f3730a68a5
Autor:
Vanesa Martínez-Valderrey, Manuel Gil-Mediavilla, Mercedes Villasana-Terradillos, Sonia Alguacil-Sánchez
Publikováno v:
Frontiers in Psychology, Vol 14 (2023)
Externí odkaz:
https://doaj.org/article/1c4cd7e64ac2499999f6ee549775f1a0
Publikováno v:
Engineering Proceedings, Vol 58, Iss 1, p 69 (2023)
Hand pose recognition presents significant challenges that need to be addressed, such as varying lighting conditions or complex backgrounds, which can hinder accurate and robust hand pose estimation. This can be mitigated by employing MediaPipe to fa
Externí odkaz:
https://doaj.org/article/61f860379960464087f027e1b32d1a24
Autor:
María Villa-Monedero, Manuel Gil-Martín, Daniel Sáez-Trigueros, Andrzej Pomirski, Rubén San-Segundo
Publikováno v:
Journal of Imaging, Vol 9, Iss 12, p 262 (2023)
Several sign language datasets are available in the literature. Most of them are designed for sign language recognition and translation. This paper presents a new sign language dataset for automatic motion generation. This dataset includes phonemes f
Externí odkaz:
https://doaj.org/article/a58ad238ce434ef7b6a8057d0b4ce81a
Autor:
Manuel Gil-Martín, María Villa-Monedero, Andrzej Pomirski, Daniel Sáez-Trigueros, Rubén San-Segundo
Publikováno v:
Sensors, Vol 23, Iss 23, p 9365 (2023)
This paper proposes, analyzes, and evaluates a deep learning architecture based on transformers for generating sign language motion from sign phonemes (represented using HamNoSys: a notation system developed at the University of Hamburg). The sign ph
Externí odkaz:
https://doaj.org/article/305cda5287cd43049dde00d55eb551ef