Zobrazeno 1 - 10
of 483
pro vyhledávání: '"Diaz-Ruiz P"'
Autor:
Morillo-Verdugo R, Lazaro-Lopez A, Alonso-Grandes E, Martin-Conde MT, Diaz-Ruiz P, Molina-Cuadrado E, Huertas-Fernandez MJ, Navarro-Aznares H, Areas Del Aguila V, Gimeno-Gracia M, Margusino-Framiñán L, Martínez-Sesmero JM
Publikováno v:
Journal of Multidisciplinary Healthcare, Vol Volume 15, Pp 2991-3003 (2022)
Ramón Morillo-Verdugo,1 Alicia Lazaro-Lopez,2 Elena Alonso-Grandes,3 Maria Teresa Martin-Conde,4 Pilar Diaz-Ruiz,5 Emilio Molina-Cuadrado,6 María José Huertas-Fernandez,7 Herminia Navarro-Aznares,8 Vera Areas Del Aguila,9 Mercedes Gimeno-Gracia,10
Externí odkaz:
https://doaj.org/article/81248a08809b4439ab8ec0e28a158f35
Multiple-Input Multiple-Output (MIMO) systems play a crucial role in fifth-generation (5G) mobile communications, primarily achieved through the utilization of precoding matrix techniques. This paper presents precoding techniques employing codebooks
Externí odkaz:
http://arxiv.org/abs/2410.02391
Autor:
You, Yurong, Phoo, Cheng Perng, Diaz-Ruiz, Carlos Andres, Luo, Katie Z, Chao, Wei-Lun, Campbell, Mark, Hariharan, Bharath, Weinberger, Kilian Q
Accurate 3D object detection is crucial to autonomous driving. Though LiDAR-based detectors have achieved impressive performance, the high cost of LiDAR sensors precludes their widespread adoption in affordable vehicles. Camera-based detectors are ch
Externí odkaz:
http://arxiv.org/abs/2404.05139
Autor:
Alfonso Mata-Bermudez, Ricardo Trejo-Chávez, Marina Martínez-Vargas, Adán Pérez-Arredondo, Maria de Los Ángeles Martínez-Cardenas, Araceli Diaz-Ruiz, Camilo Rios, Luz Navarro
Publikováno v:
Frontiers in Neuroscience, Vol 18 (2024)
Traumatic brain injury (TBI) represents a public health issue with a high mortality rate and severe neurological and psychiatric consequences. Mood and anxiety disorders are some of the most frequently reported. Primary and secondary damage can cause
Externí odkaz:
https://doaj.org/article/26b39048cc9c4080999b0a7cd6b54ef2
Autor:
Diaz-Ruiz, Carlos A., Xia, Youya, You, Yurong, Nino, Jose, Chen, Junan, Monica, Josephine, Chen, Xiangyu, Luo, Katie, Wang, Yan, Emond, Marc, Chao, Wei-Lun, Hariharan, Bharath, Weinberger, Kilian Q., Campbell, Mark
Advances in perception for self-driving cars have accelerated in recent years due to the availability of large-scale datasets, typically collected at specific locations and under nice weather conditions. Yet, to achieve the high safety requirement, t
Externí odkaz:
http://arxiv.org/abs/2208.01166
This paper focuses on the problem of decentralized pedestrian tracking using a sensor network. Traditional works on pedestrian tracking usually use a centralized framework, which becomes less practical for robotic applications due to limited communic
Externí odkaz:
http://arxiv.org/abs/2202.13237
We present a method for detecting and mapping trees in noisy stereo camera point clouds, using a learned 3-D object detector. Inspired by recent advancements in 3-D object detection using a pseudo-lidar representation for stereo data, we train a Poin
Externí odkaz:
http://arxiv.org/abs/2103.15967
Autor:
You, Yurong, Diaz-Ruiz, Carlos Andres, Wang, Yan, Chao, Wei-Lun, Hariharan, Bharath, Campbell, Mark, Weinberger, Kilian Q
Self-driving cars must detect other vehicles and pedestrians in 3D to plan safe routes and avoid collisions. State-of-the-art 3D object detectors, based on deep learning, have shown promising accuracy but are prone to over-fit to domain idiosyncrasie
Externí odkaz:
http://arxiv.org/abs/2103.14198
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