Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance
- DOI
- 10.1177/2167647x261463938
- Published
- 2026-06-30
- Container
- Big Data
- Publisher
- SAGE Publications
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1177/2167647x261463938,
title = {Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance},
author = {Pinnapureddy Manasa and Maragoni Mahendar and Purude Vaishali Narayanrao and Satwik Komuravelli and Sreena Lakhani and Shakila Basheer and Mohammad Tabrez Quasim},
year = {2026},
journal = {Big Data},
doi = {10.1177/2167647x261463938},
url = {https://doi.org/10.1177/2167647x261463938}
}RIS
TY - JOUR TI - Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance AU - Pinnapureddy Manasa AU - Maragoni Mahendar AU - Purude Vaishali Narayanrao AU - Satwik Komuravelli AU - Sreena Lakhani AU - Shakila Basheer AU - Mohammad Tabrez Quasim PY - 2026 JO - Big Data DO - 10.1177/2167647x261463938 UR - https://doi.org/10.1177/2167647x261463938 ER -
APA
Manasa, P., Mahendar, M., Narayanrao, P. V., Komuravelli, S., Lakhani, S., Basheer, S., & Quasim, M. T. (2026). Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance. Big Data. https://doi.org/10.1177/2167647x261463938
Source records
- crossref · retrieved 2026-09-25T20:47:23.213Z