Abstract. Human activity recognition (AR) has begun to mature as a field, but for AR research to thrive, large, diverse, high quality, AR data sets must be ...
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Sep 13, 2014 · In this paper we outline problems and limitations with AR data sets and describe the methodology problems we noticed, in the hope that this will ...
Sep 13, 2014 · ▫Several papers cover multiple data sets and thus. 38 data sets were analyzed. ▫Several papers utilized multiple model types and.
A competitive approach for human activity recognition on smartphones . In Proc. European Symposium on Artificial Neural Networks, Computational Intelligence, ...
Oct 18, 2021 · Human activity recognition (HAR) is a process aimed at the classification of human actions in a given period of time based on discrete ...
Despite the success of deep learning and federated learning for accurate activity recognition, there is one major limitation to the deployment of context-aware ...
General limitations with human activity recognition with deep learning, while being somewhat negligible, is that often datasets must be very large before a ...
The proposed method outperformed existing methodologies, achieving 95.48% recognition accuracy on the UCI-HAR dataset. The summary of the literature related to ...
Feb 4, 2020 · In the earlier chapters, we have presented methodologies to accomplish human activity recognition, pre-processing steps of raw data from sensors ...
May 9, 2023 · Human activity recognition (HAR) algorithms today are designed and evaluated on data collected in controlled settings, providing limited ...