2021
DOI: 10.3390/s21217278
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Human Activity Recognition: A Dynamic Inductive Bias Selection Perspective

Abstract: In this article, we study activity recognition in the context of sensor-rich environments. In these environments, many different constraints arise at various levels during the data generation process, such as the intrinsic characteristics of the sensing devices, their energy and computational constraints, and their collective (collaborative) dimension. These constraints have a fundamental impact on the final activity recognition models as the quality of the data, its availability, and its reliability, among ot… Show more

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Cited by 8 publications
(2 citation statements)
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“…Furthermore, sensor placement and dislocation can be problematic [8]. Another problem is associated to an absence of interoperability among a variety of sensor deployments [9]. Methods of the second type rely on non-wearable sensors consisting of one or multiple cameras to detect the human body.…”
Section: Introductionmentioning
confidence: 99%
“…Furthermore, sensor placement and dislocation can be problematic [8]. Another problem is associated to an absence of interoperability among a variety of sensor deployments [9]. Methods of the second type rely on non-wearable sensors consisting of one or multiple cameras to detect the human body.…”
Section: Introductionmentioning
confidence: 99%
“…Incomplete or redundant perspectives can lead to further confuse the concepts between them and to reduce the performance of the learning process. Beyond the dependencies (overlap) relating to the perspectives provided by the deployments of sensors, the phenomena themselves and the concepts which compose them often exhibit intrinsic dependencies (Silla and Freitas 2011;Essaidi, Osmani, and Rouveirol 2015;Hamidi and Osmani 2021).…”
Section: Introductionmentioning
confidence: 99%