Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance.
- DOI
- 10.1177/2167647x261463938
- Published
- 2026 Aug
- Container
- Big data
- Publisher
- Not recorded
- 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 = {Manasa P and Mahendar M and Narayanrao PV and Komuravelli S and Lakhani S and Basheer S and Tabrez Quasim M},
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 - Manasa P AU - Mahendar M AU - Narayanrao PV AU - Komuravelli S AU - Lakhani S AU - Basheer S AU - Tabrez Quasim M PY - 2026 JO - Big data DO - 10.1177/2167647x261463938 UR - https://doi.org/10.1177/2167647x261463938 ER -
APA
P, M., M, M., PV, N., S, K., S, L., S, B., & M, T. Q. (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
- pubmed · retrieved 2026-11-10T13:23:19.512Z