Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Juan A. Alvarez-Garcia"'
Autor:
Jesus Ruiz-Santaquiteria, Alberto Velasco-Mata, Noelia Vallez, Gloria Bueno, Juan A. Alvarez-Garcia, Oscar Deniz
Publikováno v:
IEEE Access, Vol 9, Pp 123815-123826 (2021)
Closed-circuit television (CCTV) systems are essential nowadays to prevent security threats or dangerous situations, in which early detection is crucial. Novel deep learning-based methods have allowed to develop automatic weapon detectors with promis
Externí odkaz:
https://doaj.org/article/01303c5ef0dd4bfa89d35be6020c22b0
Autor:
Jose L. Salazar Gonzalez, Luis Miguel Soria Morillo, Juan A. Alvarez-Garcia, Fernando Enriquez De Salamanca Ros, Antonio R. Jimenez Ruiz
Publikováno v:
IEEE Access, Vol 7, Pp 162664-162682 (2019)
In order to apply indoor localization systems in real environments it is necessary to provide an accurate location without implying a high impact on the user's normal behaviour. To achieve this goal, in this paper, a combination of battery saving tec
Externí odkaz:
https://doaj.org/article/86c1ee50798f4f6fbc339f72f4f18b22
Autor:
Juan A. Alvarez-Garcia, Jose L. Salazar-Gonzalez, Oscar Deniz Suarez, Jesus Ruiz Santaquiteria-Alegre
Publikováno v:
2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom).
Autor:
Ángel Torregrosa-Domínguez, Juan A. Álvarez-García, Jose L. Salazar-González, Luis M. Soria-Morillo
Publikováno v:
Applied Sciences, Vol 14, Iss 18, p 8198 (2024)
Gun violence is a global problem that affects communities and individuals, posing challenges to safety and well-being. The use of autonomous weapons detection systems could significantly improve security worldwide. Despite notable progress in the fie
Externí odkaz:
https://doaj.org/article/bc1f48e388674c3ebf465a8873856a07
Publikováno v:
Sensors, Vol 24, Iss 16, p 5429 (2024)
This paper presents a comprehensive approach to detect violent events in videos by combining CrimeNet, a Vision Transformer (ViT) model with structured neural learning and adversarial regularization, with an adaptive threshold sliding window model ba
Externí odkaz:
https://doaj.org/article/2f64e4688d8a4986888912fd7c00c94c
Publikováno v:
Universidad Nacional Autónoma de México
UNAM
Repositorio de Tesis DGBSDI, Dirección General de Bibliotecas y Servicios Digitales de Información, UNAM
Athenea Digital de la Facultad de Filosofía y Letras de la UNAM
UNAM
Repositorio de Tesis DGBSDI, Dirección General de Bibliotecas y Servicios Digitales de Información, UNAM
Athenea Digital de la Facultad de Filosofía y Letras de la UNAM
Fuente TESIUNAM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::1a1298d42bcf076c097f002b5f60fb1a
https://ru.dgb.unam.mx/handle/DGB_UNAM/TES01000805280
https://ru.dgb.unam.mx/handle/DGB_UNAM/TES01000805280
Autor:
Hristijan Gjoreski, Simon Kozina, Matjaz Gams, Mitja Lustrek, Juan Antonio Alvarez-Garcia, null Jin-Hyuk Hong, Julian Ramos, Anind K. Dey, Maurizio Bocca, Neal Patwari
Publikováno v:
IEEE Pervasive Computing. 14:70-77
Ensuring the validity and usability of activity recognition approaches requires agreement on a set of standard evaluation methods. Due to the diversity of the sensors and other hardware employed, however, designing, implementing, and accepting standa
Autor:
Damián Fernández-Cerero, Jorge Yago Fernández-Rodríguez, Juan A. Álvarez-García, Luis M. Soria-Morillo, Alejandro Fernández-Montes
Publikováno v:
Sensors, Vol 19, Iss 13, p 3026 (2019)
The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads,
Externí odkaz:
https://doaj.org/article/ae7b140560e2469d942b6ead221fd1f3