Zobrazeno 1 - 10
of 102
pro vyhledávání: '"Uwe Handmann"'
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 4, Iss 1, Pp 22-41 (2022)
Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages in achievin
Externí odkaz:
https://doaj.org/article/ac7b08eb38104990b2f7ccb32fab2e06
Publikováno v:
EAI Endorsed Transactions on Smart Cities, Vol 5, Iss 16 (2021)
INTRODUCTION: Sorting a huge stream of waste accurately within a short period can be done with the support of digitalization, particularly Artificial Intelligence, instead of traditional methods. The overlap of Artificial Intelligence and Circular Ec
Externí odkaz:
https://doaj.org/article/01e00759dcff4448859377e63363cde7
Publikováno v:
Sensors, Vol 19, Iss 1, p 59 (2018)
In this review, we describe current Machine Learning approaches to hand gesture recognition with depth data from time-of-flight sensors. In particular, we summarise the achievements on a line of research at the Computational Neuroscience laboratory a
Externí odkaz:
https://doaj.org/article/e851dddc737c497cbfbac8138b62aeef
Publikováno v:
2023 IEEE Conference on Technologies for Sustainability (SusTech).
Autor:
Uwe Handmann, Nermeen Abou Baker
Publikováno v:
2022 IEEE Sensors.
Publikováno v:
2022 26th International Conference on Pattern Recognition (ICPR).
Publikováno v:
Machine Learning and Knowledge Extraction; Volume 4; Issue 1; Pages: 22-41
Transfer learning is a machine learning technique that uses previously acquired knowledge from a source domain to enhance learning in a target domain by reusing learned weights. This technique is ubiquitous because of its great advantages in achievin
Publikováno v:
ESANN 2022 proceedings.
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031159183
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::74083bc786f30621f3bd12c32666e208
https://doi.org/10.1007/978-3-031-15919-0_57
https://doi.org/10.1007/978-3-031-15919-0_57
Publikováno v:
EAI Endorsed Transactions on Smart Cities, Vol 5, Iss 16 (2021)
INTRODUCTION: Sorting a huge stream of waste accurately within a short period can be done with the support of digitalization, particularly Artificial Intelligence, instead of traditional methods. The overlap of Artificial Intelligence and Circular Ec