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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Malik A. Alsaedi
Al-Iraqia University
Electrical & Electronics Engineering

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Journal : Bulletin of Electrical Engineering and Informatics

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Development of 3D convolutional neural network to recognize human activities using moderate computation machine Malik A. Alsaedi; Abdulrahman Saeed Mohialdeen; Baraa Munqith Albaker
Bulletin of Electrical Engineering and Informatics Vol 10, No 6: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i6.2802

Abstract

Human activity recognition (HAR) is recently used in numerous applications including smart homes to monitor human behavior, automate homes according to human activities, entertainment, falling detection, violence detection, and people care. Vision-based recognition is the most powerful method widely used in HAR systems implementation due to its characteristics in recognizing complex human activities. This paper addresses the design of a 3D convolutional neural network (3D-CNN) model that can be used in smart homes to identify several numbers of activities. The model is trained using KTH dataset that contains activities like (walking, running, jogging, handwaving handclapping, boxing). Despite the challenges of this method due to the effectiveness of the lamination, background variation, and human body variety, the proposed model reached an accuracy of 93.33%. The model was implemented, trained and tested using moderate computation machine and the results show that the proposal was successfully capable to recognize human activities with reasonable computations.
Co-Authors Abdulrahman Saeed Mohialdeen Arwa A. Moosa Baraa Munqith Albaker Hussein Jumma Jabir Mays Afif Anaee