Zobrazeno 1 - 10
of 107
pro vyhledávání: '"Nguyen, Sao"'
Autor:
Bouchabou, Damien, Nguyen, Sao Mai
Within the evolving landscape of smart homes, the precise recognition of daily living activities using ambient sensor data stands paramount. This paper not only aims to bolster existing algorithms by evaluating two distinct pretrained embeddings suit
Externí odkaz:
http://arxiv.org/abs/2412.19732
Analyzing human motion is an active research area, with various applications. In this work, we focus on human motion analysis in the context of physical rehabilitation using a robot coach system. Computer-aided assessment of physical rehabilitation e
Externí odkaz:
http://arxiv.org/abs/2408.02855
Publikováno v:
IJCNN 2024
While automatic monitoring and coaching of exercises are showing encouraging results in non-medical applications, they still have limitations such as errors and limited use contexts. To allow the development and assessment of physical rehabilitation
Externí odkaz:
http://arxiv.org/abs/2407.00521
Autor:
Annabi, Louis, Nguyen, Sao Mai
Publikováno v:
2023 IEEE International Conference on Development and Learning (ICDL), Nov 2023, Macau, China. pp.176-181
This paper addresses the importance of Knowledge Structure (KS) and Knowledge Tracing (KT) in improving the recommendation of educational content in intelligent tutoring systems. The KS represents the relations between different Knowledge Components
Externí odkaz:
http://arxiv.org/abs/2402.01672
This early-stage research work aims to improve online human-robot imitation by translating sequences of joint positions from the domain of human motions to a domain of motions achievable by a given robot, thus constrained by its embodiment. Leveragin
Externí odkaz:
http://arxiv.org/abs/2402.05115
Publikováno v:
ICLR 2024
Goal representation affects the performance of Hierarchical Reinforcement Learning (HRL) algorithms by decomposing the complex learning problem into easier subtasks. Recent studies show that representations that preserve temporally abstract environme
Externí odkaz:
http://arxiv.org/abs/2401.09870
Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. However, the existing Hierarchical Reinforcement Learning (HRL) approac
Externí odkaz:
http://arxiv.org/abs/2309.07675
Publikováno v:
Intrinsically Motivated Open-ended Learning IMOL 2023, Sep 2023, Paris, France
Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. However, the existing Hierarchical Reinforcement Learning (HRL) approac
Externí odkaz:
http://arxiv.org/abs/2309.07168
Publikováno v:
KI - K{\"u}nstliche Intelligenz, Springer Nature, 2021, 35 (81-90)
Multi-task learning by robots poses the challenge of the domain knowledge: complexity of tasks, complexity of the actions required, relationship between tasks for transfer learning. We demonstrate that this domain knowledge can be learned to address
Externí odkaz:
http://arxiv.org/abs/2202.10222
Generally, Human Activity Recognition (HAR) consists of monitoring and analyzing the behavior of one or more persons in order to deduce their activity. In a smart home context, the HAR consists of monitoring daily activities of the residents. Thanks
Externí odkaz:
http://arxiv.org/abs/2112.11232