Content oriented 3D-CNN sequence learning architecture for academic activities recognition using a realistic CAD dataset

Content oriented 3D-CNN sequence learning architecture for academic activities recognition using a realistic CAD dataset

Abstract In computer vision, video analytic researchers have been developing techniques for human activity recognition in several application domains. Academic institutions are in possession of rich video repository generated by the surveillance system in respective campuses. One major requirement i...

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Bibliographic Details
Main Authors: Muhammad Wasim, Imran Ahmed, Naveed Abbas, Tanzila Saba, Faten S. Alamri, Alex Elyassih, Amjad Rehman
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Long short-term memory
Activity recognition
Deep learning
RNN
Video surveillance
3D CNN
Online Access:https://doi.org/10.1038/s41598-025-07620-3
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https://doi.org/10.1038/s41598-025-07620-3

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