Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Agnes Tegen"'
Autor:
Jan A. Persson, Joseph Bugeja, Paul Davidsson, Johan Holmberg, Victor R. Kebande, Radu-Casian Mihailescu, Arezoo Sarkheyli-Hägele, Agnes Tegen
Publikováno v:
Applied Sciences, Vol 13, Iss 11, p 6516 (2023)
This paper concerns the novel concept of an Interactive Dynamic Intelligent Virtual Sensor (IDIVS), which extends virtual/soft sensors towards making use of user input through interactive learning (IML) and transfer learning. In research, many studie
Externí odkaz:
https://doaj.org/article/b1eadea1d6e24ebaa95bf1c1f0b84523
Publikováno v:
Sensors, Vol 19, Iss 3, p 477 (2019)
Although the availability of sensor data is becoming prevalent across many domains, it still remains a challenge to make sense of the sensor data in an efficient and effective manner in order to provide users with relevant services. The concept of vi
Externí odkaz:
https://doaj.org/article/971f799996834d58a38ba7446f5c432a
Publikováno v:
2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::493058921ae6d7e7b18fc133d8e8aebb
https://doi.org/10.1109/icmla52953.2021.00197
https://doi.org/10.1109/icmla52953.2021.00197
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676605
ECML/PKDD (2)
ECML/PKDD (2)
In interactive machine learning, human users and learning algorithms work together in order to solve challenging learning problems, e.g. with limited or no annotated data or trust issues. As annotating data can be costly, it is important to minimize
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25728a177c5683b44818da0a5abdba1a
https://doi.org/10.1007/978-3-030-67661-2_9
https://doi.org/10.1007/978-3-030-67661-2_9
Publikováno v:
NordiCHI
Machine Learning (ML) has been a prominent area of research within Artificial Intelligence (AI). ML uses mathematical models to recognize patterns in large and complex data sets to aid decision making in different application areas, such as image and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d49ef26be3c161b2189e15977fa15ca2
https://doi.org/10.1145/3419249.3421236
https://doi.org/10.1145/3419249.3421236
Correction to: Activity recognition through interactive machine learning in a dynamic sensor setting
Publikováno v:
Personal and Ubiquitous Computing.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29cce468dba68e25be4e28f0f03ecddc
https://doi.org/10.1007/s00779-020-01465-5
https://doi.org/10.1007/s00779-020-01465-5
Autor:
Agnes Tegen
With the Internet of Things paradigm, the data generated by the rapidly increasing number of connected devices lead to new possibilities, such as using machine learning for activity recognition in smart environments. However, it also introduces sever
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34e0e5059ad9586ae8f3c69db8d768fa
https://doi.org/10.24834/isbn.9789178770854
https://doi.org/10.24834/isbn.9789178770854
Publikováno v:
IOT
The advances in Internet of Things lead to an increased number of devices generating and streaming data. These devices can be useful data sources for Activity Recognition by using Machine Learning. However, as the set of available sensors may vary ov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b40767061e4a07479de8e5ace0b7f7d
https://doi.org/10.1145/3365871.3365881
https://doi.org/10.1145/3365871.3365881
Publikováno v:
UbiComp/ISWC Adjunct
With advances in Internet of Things many opportunities arise if the challenges of continual learning in a multimodal setting can be tackled. One common issue in Online Learning is to obtain labelled data, as this generally is costly. Active Learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::423d343cfc4bf62e2040f6a328fca073
https://doi.org/10.1145/3341162.3345603
https://doi.org/10.1145/3341162.3345603
Publikováno v:
Sensors (Basel, Switzerland)
Sensors, Vol 19, Iss 3, p 477 (2019)
Sensors
Volume 19
Issue 3
Sensors, Vol 19, Iss 3, p 477 (2019)
Sensors
Volume 19
Issue 3
Although the availability of sensor data is becoming prevalent across many domains, it still remains a challenge to make sense of the sensor data in an efficient and effective manner in order to provide users with relevant services. The concept of vi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::98c8f3ea0bfeacd232ac2ad620a691c2
http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-2628
http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-2628