… However, proposing sufficiently robust online activity recognition approach in smart … online
application of Hierarchical Hidden Markov Model in order to detect the current activity on the …

… Machine learning techniques like decision trees, K-nearest neighbours, support vector
machines, hidden markov models are reviewed for HAR and later the survey for deep neural …

… human postures estimation, efficient body parts modelling, the … an entropy Markov model
for human activity recognition from … , SVM, Hidden Markov model (HMM) and CNN, for activity …

… Figure 5 represents that HMMs are widely used in the area of speech recognition (25%
papers) and human activity recognition (25% papers). Additionally, HMMs are also used in the …

… HIR systems are also proposed for security reasons [11], such as a Fuzzy logic based
human activity recognition system, which was proposed in [12]. A Hidden Markov Model [HMM] …

… accuracy, that is, 83%–90%; Olguin et al. used Hidden Markov model (HMM) as a classification
model to compare the effects of different sensor positions on the final classification results…

… Multi-modal human action recognition using deep neural networks fusing image and inertial
sensor data. In Proceedings of the IEEE International Conference on Multisensor Fusion …

… In this paper, we present a human activity recognition model that acquires signal data from
… to use this model was to overcome the concept of the conventional hidden Markov model (…

… the broad application of sensors, human activity recognition (… have shown great application
value. Owing to the initiative of … In contrast, graphical models such as hidden Markov models …

… Gesture plays the most significant role in conveying physical human actions for nonverbal
communication. Mostly, hand and face expressions are used as gestures for interactions such …