Deep Learning Trends for Video Based Activity Recognition: A Survey
Conclusion: Deep networks can dramatically improve the recognition performance because of its hierarchical nature to exploit the video frame structure in reducing the search space of the learning model. This motivated us to provide a comprehensive survey of the state-of-art deep models for recognizing human actions/activities.
Keywords: Activity recognition; algorithams; convolution; deep learning; handcrafted features; spatio-temporal dimension
Document Type: Review Article
Publication date: 01 December 2018
The International Journal of Sensors, Wireless Communication and Control publishes timely research articles, reviews and communications on these three strongly related areas, with emphasis on networked control systems whose sensors are interconnected via wireless communication networks.
The emergence of high speed wireless network technologies allows a cluster of devices to be linked together economically to form a distributed system. Wireless communication is playing an increasingly important role in such distributed systems. Transmitting sensor measurements and control commands over wireless links allows rapid deployment, flexible installation, fully mobile operation and prevents the cable wear and tear problem in industrial automation, healthcare and environmental assessment. Wireless networked systems has raised and continues to raise fundamental challenges in the fields of science, engineering and industrial applications, hence, more new modelling techniques, problem formulations and solutions are required.
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