Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Huu-Thiet Nguyen"'
Publikováno v:
IEEE Access, Vol 11, Pp 21992-22006 (2023)
Deep Learning (DL) systems are difficult to analyze and proving convergence of DL algorithms like backpropagation is an extremely challenging task as it is a highly non-convex and high-dimensional problem. When using DL algorithms in robotic systems,
Externí odkaz:
https://doaj.org/article/862b5c4de3e449f9907ca5edac21261e
Publikováno v:
IEEE Access, Vol 10, Pp 14270-14287 (2022)
As research attention in deep learning has been focusing on pushing empirical results to a higher peak, remarkable progress has been made in the performance race of machine learning applications in the past years. Yet deep learning based on artificia
Externí odkaz:
https://doaj.org/article/062b1e56620a41098f69e09810f13334
Deep learning (DL) has achieved great success in many applications, but it has been less well analyzed from the theoretical perspective. The unexplainable success of black-box DL models has raised questions among scientists and promoted the emergence
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::094afe556e077befab82566c1c65ba08
https://hdl.handle.net/10356/159370
https://hdl.handle.net/10356/159370
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
ICRA
The inner/low-level control loop of most industrial robotic manipulators is protected from any modification by a closed control architecture. The only way to specify joint inputs to them is through position or velocity commands. Furthermore, the inne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ad607a36a2fa19a66ab8a969e01fa94
https://doi.org/10.1109/icra48506.2021.9562112
https://doi.org/10.1109/icra48506.2021.9562112
Autor:
Chien Chern Cheah, Huu-Thiet Nguyen
Publikováno v:
IECON
Modeling is an important task in classic control system design. However, as the robotics systems are getting more complex, the modeling tasks using fundamental physical principles are becoming more difficult. One of the emerging approaches to avoid d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3bc433957fbb437381ec285b834db180
https://doi.org/10.1109/iecon43393.2020.9254442
https://doi.org/10.1109/iecon43393.2020.9254442
Publikováno v:
Web of Science
AIM
AIM
This paper presents an iterative learning algorithm for functional approximation, with applications to the robot kinematics problems. Various approaches have been proposed in the literature to approximate the kinematic models of robots. However, most
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f355cd98744a3d183c89f50734cf0ce
https://publons.com/wos-op/publon/47063741/
https://publons.com/wos-op/publon/47063741/