# Review on Deep Learning Approaches for Anomaly Event Detection in Video Surveillance

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/review-on-deep-learning-approaches-for-anomaly-event-detection-in-video/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sabah Abdulazeez Jebur,Khalid Ali Hussein,Haider K. Hoomod,Laith Alzubaidi,José Santamaría |
| Citations | 65 |
| DOI | 10.3390/electronics12010029 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2079-9292/12/1/29/pdf?version=1671698188 |
| OpenAlex ID | https://openalex.org/W4312116982 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Sabah Abdulazeez Jebur](https://scholariq.org/researchers/sabah-abdulazeez-jebur/)

## Paper journal

- [Electronics](https://scholariq.org/journals/electronics/)

## Paper primary topic

- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)

## Paper topics

- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [Network Security and Intrusion Detection](https://scholariq.org/topics/network-security-and-intrusion-detection/)
- [Data-Driven Disease Surveillance](https://scholariq.org/topics/data-driven-disease-surveillance/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.