Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Niall O' Mahony"'
Publikováno v:
Communications in Computer and Information Science ISBN: 9783031264375
There have been many developments in recent years on the exploitation of non-Euclidean geometry for the better representation of the relation between subgroups in datasets. Great progress has been made in this field of Disentangled Representation Lea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0583ab098b37926c16c1824f48410e7a
https://doi.org/10.1007/978-3-031-26438-2_38
https://doi.org/10.1007/978-3-031-26438-2_38
Publikováno v:
Procedia Manufacturing. 38:178-185
This paper will review specific aspects of the edge computing architecture and its correlation to industrial applications as part of a literal revision, performed to provide evidences supporting the use of edge solutions in challenging conditions whi
Publikováno v:
Procedia Computer Science. 155:276-281
This research investigates the impact of edge agents on industrial plants in the era of the Internet of Things (IoT) and the increasing availability of internet connection. This paper proposes ‘Edge Agent’ a holistic solution to managing many dev
Autor:
Niall O' Mahony, Lenka Krpalkova, Anderson Carvalho, Gustavo Velasco Hernandez, Daniel Riordan, Sean Campbell, Joseph Walsh, Suman Harapanahalli
Publikováno v:
Procedia Manufacturing. 38:186-193
Deep Learning has great achievements in computer vision for various classification and regression tasks. The automation of tasks such as component sorting, bin-picking and anomaly detection may be of great use in the process industry. However, most m
Autor:
Suman Harapanahalli, Gustavo Velasco Hernandez, Joseph Walsh, Sean Campbell, Niall O' Mahony, Daniel Riordan
Publikováno v:
Procedia Manufacturing. 38:1524-1531
Navigating through unstructured environments is a basic capability of intelligent creatures, and thus is of fundamental interest in this research. Navigation is a complex task that relies on developing an internal representation of space, grounded by
Autor:
Anderson Carvalho, Lenka Krpalkova, Daniel Riordan, Niall O' Mahony, Joseph Walsh, Sean Campbell
Publikováno v:
IFAC-PapersOnLine. 52:312-317
3D vision systems will play an important role in next-generation dairy farming due to the sensing capabilities they provide in the automation of animal husbandry tasks such as the monitoring, herding, feeding, milking and bedding of animals. This pap
Publikováno v:
Proceedings of the 2020 4th International Symposium on Computer Science and Intelligent Control.
Due to the increasing availability of internet connection both industrial and agricultural environments have experienced an expressive increase in the number of IoT devices for the last few years. This paper exposes an extensive architecture investig
Autor:
Sean Campbell, Anderson Carvalho, Lenka Krpalkova, Suman Harapanahalli, Gustavo Velasco-Hernandez, Niall O' Mahony, Joseph Walsh, Daniel Riordan
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030177942
Deep Learning has pushed the limits of what was possible in the domain of Digital Image Processing. However, that is not to say that the traditional computer vision techniques which had been undergoing progressive development in years prior to the ri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::06e02d3262758114fb68546498e0ed6e
https://doi.org/10.1007/978-3-030-17795-9
https://doi.org/10.1007/978-3-030-17795-9
Autor:
Niall O' Mahony, Daniel Riordan, Joseph Walsh, Conor Ryan, Sean Campbell, Lenka Krpalkova, Aidan Murphy
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030010560
IntelliSys (2)
IntelliSys (2)
This paper will review the progress which has been made in Artificial Intelligence and Computer Vision particularly in 3D computer vision. There has been a lot of activity in the development of both hardware and software in 3D imaging systems which w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b0b6222099a0055543fdaafcbdfedfd9
https://doi.org/10.1007/978-3-030-01057-7_59
https://doi.org/10.1007/978-3-030-01057-7_59
Machine learning algorithms for estimating powder blend composition using near infrared spectroscopy
Publikováno v:
2018 2nd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS).
This paper presents a NIRS based real time continuous monitoring of powder blend composition which has widespread applications such as the pharmaceutical industry. The paper extends the implementation of several machine learning methodologies applied