… an activity recognition approach apposite for a smart home … to extract features across
multiple datasets of different type, … We analyze the performance of the proposed approach for …

… on the real-world smart home datasets. Our results suggest that extracting latent features
from sensor data … We plan to analyze these activities, and improve our method in the future. …

… automatic recognition of human activities through the analysis of … A dataset similar to the
actual use case and trained on the … defined features can perform well in recognizing one activity, …

… the actions, characteristics, and goals of one or more … human behavior recognition through
a mobile dataset [36] to … Since the use of accuracy only is insufficient for analysis and …

… smart home activity recognition dataset (the CASAS Milan … Second, we analyze the
effectiveness of each explanation … , we analyze the outputs of \(O_{LIME}\) across all M features …

… , for smartphone-based human activity recognition. It comprises data … an optimal computational
and analysis pipeline which … 64 features that proved to perform best with two datasets was …

… These projects investigated the analysis of daily activities; trying to induce behavioral patterns
… dataset that contains 10 different activities with their associated sound features. The final …

… activities in multitenant smart home scenarios. We propose a sensor data contribution significance
analysis … sensors in different datasets to the activity recognition standard as calculated …

… analysis (PCA) [23] to satisfy this constraint. In this method, the covariance matrix of the
extracted features from a dataset is … Another smart-home open dataset called activity recognition …

… datasets commonly employed in activity recognition task … installed in the smart home, the
dimension of the features vector \(… In summary, the IncSim is the only method where the training …