… rate, temperature) and RFID tags to gather a person’s behavioural information. Activity
recognition based on wearable sensors has been extensively used in the recognition of human …

… a Action recognition task infers an action category from a video containing complete action
execution, while b action prediction task … The label could be an action category (early action …

… Action recognition based on skeleton data has recently witnessed increasing attention and
progress. State-of-theart approaches adopting Graph Convolutional networks (GCNs) can …

… review of different activity and behaviour analysis methods to … a generic deep framework
for activity recognition based on … and compound events in a unified framework. They offered a …

… activity recognition based on the dynamic Bayesian network model. Furthermore, Choi and
Savarese [4] presented a coherent, discriminative framework … predictions and measurements. …

… In order to further improve the dense prediction performance, we propose the post-correction
algorithm for the dense prediction results on the basis of the activity misalignment analysis. …

… In this paper, we propose a unified framework to model human action for both recognition …
In this paper, a video prediction is considered as correct if both the predicted action label and …

… performance analysis of the proposed method with and without DAFU network followed by
EfficientNetB0 backbone for activity … Here, the prediction of the proposed method and their …

… In the behavioral analysis industry, HAR is used to monitor and identify family behavior [8].
In the … With these advantages, human activity recognition based on wearable sensors has …

… many practical applications such as behavioural analysis [2], … by activity recognition based
on the estimated key points [20]… , the prediction errors from both pose estimation and activity …