A deep genetic algorithm for human activity recognition leveraging fog computing frameworks

Author:

Subramanian R. RajaORCID,Vasudevan V.

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference67 articles.

1. Human action recognition by learning spatiotemporal features with deep neural networks;Wang;IEEE Access,2018

2. Sensor data fusion and big mobility data analytics for activity recognition;Stojanovic,2019

3. Y. Liu, L. Nie, L. Han, L. Zhang, D.S. Rosenblum, Action2Activity: recognizing complex activities from sensor data, in: Proceedings of the 24th International Conference on Artificial Intelligence, 2015, pp. 1617–1623.

4. From action to activity: Sensor-based activity recognition;Liu;Neurocomputing,2016

5. L. Liu, L. Cheng, Y. Liu, Y. Jia, D.S. Rosenblum, Recognizing complex activities by a probabilistic interval-based model, in: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016, pp. 1266–1272.

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