Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ignacio Diaz-Cano"'
Publikováno v:
Machines, Vol 12, Iss 7, p 447 (2024)
This paper presents a novel approach for extracting 3D weld point information using a two-stage deep learning pipeline based on readily available 2D RGB cameras. Our method utilizes YOLOv8s for object detection, specifically targeting vertices, follo
Externí odkaz:
https://doaj.org/article/dd2c82dbe453447a8591a6d5376315c9
Publikováno v:
Revista Iberoamericana de Automática e Informática Industrial RIAI, Vol 19, Iss 2, Pp 154-163 (2021)
La visión artificial está cobrando cada día más auge en el mundo de la robótica industrial, ya que es necesario realizar tareas cada vez más precisas y autónomas, por lo que se necesita un posicionamiento del robot más exacto. Para ello se pr
Externí odkaz:
https://doaj.org/article/7efd831f393944f8961304e204a673d0
Autor:
Francisco-Javier Badesa, Fernando M. Quintana, Ignacio Diaz-Cano, Arturo Morgado-Estevez, Pedro L. Galindo, Miguel Lopez-Fuster
Publikováno v:
Industrial Robot: the international journal of robotics research and application. 49:391-401
Fillet welding is one of the most widespread types of welding in the industry, which is still carried out manually or automated by contact. This paper aims to describe an online programming system for noncontact fillet welding robots with U and L sha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4305927c8a0c8448dd1c19245cbe0618
https://doi.org/10.1108/ir-07-2021-0137
https://doi.org/10.1108/ir-07-2021-0137
Publikováno v:
14th International Conference on Computational Intelligence in Security for Information Systems and 12th International Conference on European Transnational Educational (CISIS 2021 and ICEUTE 2021) ISBN: 9783030878719
CISIS-ICEUTE
CISIS-ICEUTE
Communication networks and systems are continuously threatened by a great variety of cybersecurity attacks coming from new malware that targets old and new systems’ vulnerabilities. In this sense, Intrusion Detection Systems (IDSs) and, specificall
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f8326b2573de5d6979f69cd7847a8b8
https://doi.org/10.1007/978-3-030-87872-6_12
https://doi.org/10.1007/978-3-030-87872-6_12
This work presents Reliable-NIDS (R-NIDS), a novel methodology for Machine Learning (ML) based Network Intrusion Detection Systems (NIDSs) that allows ML models to work on integrated datasets, empowering the learning process with diverse information
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::43b62b28ee2422d089be0d7a95f44097
Publikováno v:
Applied Sciences
Volume 10
Issue 5
Applied Sciences, Vol 10, Iss 5, p 1775 (2020)
Appl. Sci. 2020, 10(5), 1775
RODIN. Repositorio de Objetos de Docencia e Investigación de la Universidad de Cádiz
instname
Volume 10
Issue 5
Applied Sciences, Vol 10, Iss 5, p 1775 (2020)
Appl. Sci. 2020, 10(5), 1775
RODIN. Repositorio de Objetos de Docencia e Investigación de la Universidad de Cádiz
instname
Presently, we are living in a hyper-connected world where millions of heterogeneous devices are continuously sharing information in different application contexts for wellness, improving communications, digital businesses, etc. However, the bigger th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f184786a625601ebd760d90ef908a157
Autor:
Arturo Morgado-Estevez, Francisco J. Abad-Fraga, Pedro Chavera, José Andrés Soto-Núñez, Ignacio Diaz-Cano, Pedro L. Galindo, Jose-Luis Aparicio-Rodriguez, Carlos Rioja-del-Rio
Publikováno v:
ROBOT 2017: Third Iberian Robotics Conference ISBN: 9783319708355
ROBOT (2)
ROBOT (2)
This paper presents an automated robotic welding system adapted for shipbuilding in large shipyards. This solution has been devised in the shipyard of Navantia located in the south of Spain, in the context of ROBOT FASE II R&D project. It also presen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c801da8f48b0131531eb5387d64e9a39
https://doi.org/10.1007/978-3-319-70836-2_5
https://doi.org/10.1007/978-3-319-70836-2_5