Supervised and Self-Supervised Learning for Assembly Line Action Recognition

Supervised and Self-Supervised Learning for Assembly Line Action Recognition

The safety and efficiency of assembly lines are critical to manufacturing, but human supervisors cannot oversee all activities simultaneously. This study addresses this challenge by performing a comparative study to construct an initial real-time, semi-supervised temporal action recognition setup fo...

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Bibliographic Details
Main Authors: Christopher Indris, Fady Ibrahim, Hatem Ibrahem, Götz Bramesfeld, Jie Huo, Hafiz Mughees Ahmad, Syed Khizer Hayat, Guanghui Wang
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Journal of Imaging
Subjects:
computer vision
action recognition
temporal action localization
semi-supervised learning
supervised learning
real-time feature extraction
Online Access:https://www.mdpi.com/2313-433X/11/1/17
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