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pro vyhledávání: '"Amirat, Yacine"'
The performance of Human Activity Recognition (HAR) models, particularly deep neural networks, is highly contingent upon the availability of the massive amount of annotated training data which should be sufficiently labeled. Though, data acquisition
Externí odkaz:
http://arxiv.org/abs/2012.03682
Publikováno v:
In Engineering Applications of Artificial Intelligence August 2023 123 Part B
Publikováno v:
In Information Sciences June 2023 631:468-486
Publikováno v:
In Engineering Applications of Artificial Intelligence February 2023 118
Endowing the robotic systems with cognitive capabilities for recognizing daily activities of humans is an important challenge, which requires sophisticated and novel approaches. Most of the proposed approaches explore pattern recognition techniques w
Externí odkaz:
http://arxiv.org/abs/1809.07624
Publikováno v:
In Neurocomputing 21 August 2022 500:649-661
Autor:
Kordestani, Hossain, Mojarad, Roghayeh, Chibani, Abdelghani, Barkaoui, Kamel, Amirat, Yacine, Zahran, Wagdy
Publikováno v:
In Expert Systems With Applications 30 December 2021 186
Publikováno v:
Theory and Practice of Logic Programming 16 (2016) 325-352
Action languages have emerged as an important field of Knowledge Representation for reasoning about change and causality in dynamic domains. This article presents Cerbere, a production system designed to perform online causal, temporal and epistemic
Externí odkaz:
http://arxiv.org/abs/1512.04358
Publikováno v:
In IFAC PapersOnLine 2020 53(2):8525-8530
Publikováno v:
IEEE Transactions on Automation Science and Engineering, Volume: 10, Issue: 3, July 2013, Pages: 829-835
Using supervised machine learning approaches to recognize human activities from on-body wearable accelerometers generally requires a large amount of labelled data. When ground truth information is not available, too expensive, time consuming or diffi
Externí odkaz:
http://arxiv.org/abs/1312.6965