Zobrazeno 1 - 10
of 63
pro vyhledávání: '"Escobar, Amado"'
Autor:
Jose M. Celis-Peñaranda, Christian D. Escobar-Amado, Sergio B. Sepúlveda-Mora, Sergio A. Castro-Casadiego, Byron Medina-Delgado, Dinael Guevara-Ibarra
Publikováno v:
TecnoLógicas, Vol 23, Iss 47, Pp 121-136 (2020)
In this study, factorial experiments were conducted in two different scenarios to design a Wireless Sensor Network for monitoring a cocoa crop in a rural area in Colombia. Node sensors measured temperature, relative humidity, soil moisture, Ultra-Vio
Externí odkaz:
https://doaj.org/article/846a8e20a09741aba92c88c528846699
Akademický článek
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Autor:
Christian D. Escobar-Amado, Preston S. Wilson, Tracianne B. Neilsen, Michael J. Buckingham, Mohsen Badiey, William S. Hodgkiss, Jie Yang, David P. Knobles
Publikováno v:
IEEE Journal of Oceanic Engineering. 47:553-564
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdf11274c02475ee9968631f68c54b45
https://doi.org/10.1109/joe.2021.3091846
https://doi.org/10.1109/joe.2021.3091846
Publikováno v:
IEEE Journal of Oceanic Engineering; January 2024, Vol. 49 Issue: 1 p133-144, 12p
Publikováno v:
The Journal of the Acoustical Society of America. 151:299-309
Bearded seals vocalizations are often analyzed manually or by using automatic detections that are manually validated. In this work, an automatic detection and classification system (DCS) based on convolutional neural networks (CNNs) is proposed. Bear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea5593d96691b9ac0b54532e782308fc
https://doi.org/10.1121/10.0009256
https://doi.org/10.1121/10.0009256
Autor:
Escobar-Amado, Christian David1 christiandavidea@ufps.edu.co, Celis-Peñaranda, Jose Miguel1 josemiguelcp@ufps.edu.co, Sepúlveda-Mora, Sergio Basilio1 sergio.sepulveda@ufps.edu.co, Castro-Casadiego, Sergio Alexander1 sergio.castroc@ufps.edu.co, Medina-Delgado, Byron1 byronmedina@ufps.edu.co, Guevara, Dinael1 dinaelgi@ufps.edu.co
Publikováno v:
INGENIARE - Revista Chilena de Ingeniería. Apr-Jun2021, Vol. 29 Issue 2, p285-296. 12p.
Autor:
David P. Knobles, Christian D. Escobar-Amado, William S. Hodgkiss, David F. Van Komen, Tracianne B. Neilsen, Jhon A. Castro-Correa, Mohsen Badiey
Publikováno v:
The Journal of the Acoustical Society of America. 150:1434-1447
Merchant ship-radiated noise, recorded on a single receiver in the 360-1100 Hz frequency band over 20 min, is employed for seabed classification using an ensemble of deep learning (DL) algorithms. Five different convolutional neural network architect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d412df8a32ebe354195ffd72c96e8dce
https://doi.org/10.1121/10.0005936
https://doi.org/10.1121/10.0005936
Autor:
Dinael Guevara, Sergio A Castro-Casadiego, Byron Medina-Delgado, Jose M. Celis-Peñaranda, Christian D. Escobar-Amado, Sergio Basilio Sepúlveda-Mora
Publikováno v:
Ingeniare. Revista chilena de ingeniería. 29:285-296
espanolPara solucionar el problema de los nodos huerfanos en una topologia tipo arbol en una red ZigBee, se ha desarrollado un algoritmo basado en nodos hibridos compuesto por un modulo XBee S2C configurado en modo API con escape conectado a un micro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad80cfad44a683dbebdb84795cd26976
https://doi.org/10.4067/s0718-33052021000200285
https://doi.org/10.4067/s0718-33052021000200285
Autor:
Mason C. Acree, David P. Knobles, Jhon A. Castro-Correa, William S. Hodgkiss, D F Van Komen, Christian D. Escobar-Amado, Tracianne B. Neilsen, Mohsen Badiey
Publikováno v:
The Journal of the Acoustical Society of America. 149:692-705
While source localization and seabed classification are often approached separately, the convolutional neural networks (CNNs) in this paper simultaneously predict seabed type, source depth and speed, and the closest point of approach. Different CNN a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc0e92169eb0fe17f4afafb48dd98e95
https://doi.org/10.1121/10.0003361
https://doi.org/10.1121/10.0003361
Autor:
Jose M Celis-Peñaranda, Christian D Escobar-Amado, Sergio B Sepulveda-Mora, Sergio A Castro-Casadiego, Byron Medina-Delgado, Jhon J Ramírez-Mateus
Publikováno v:
Ingeniería y Ciencia, Vol 12, Iss 24 (2016)
Para optimizar el flujo vehicular en una intersección vial se diseñaron un algoritmo de control adaptativo y una base de datos que apoya la depuración del rendimiento del controlador, ambos alojados en el sistema embebido Raspberry Pi B+. El desem
Externí odkaz:
https://doaj.org/article/8929797447c5456cb8022142043cce30