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Activity detection of untrimmed CCTV ATM footage using 3D convolutional neural network

2020 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2020, Page: 357-362
2020
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Conference Paper Description

This paper presents an approach to temporal human activity detection using the proposal then classification framework, which is one of the frameworks for temporal activity detection. The goal of this research is to detect and recognize certain activities at the ATM. We propose an activity detection method using a 3D convolutional neural network (3D CNN). Our proposed method achieved performance with the accuracy score of 93.94%, a precision of 96.36%, a recall of 93.94%, and an f-score of 93.69%.

Bibliographic Details

Aldi Hilman Ramadhani; Dina Chahyati

Institute of Electrical and Electronics Engineers (IEEE)

Computer Science

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