# Deployable AI for Public Safety: Weapon Detection in Challenging CCTV Scenarios

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deployable-ai-for-public-safety-weapon-detection-in-challenging-cctv-scenarios/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Charukesh Panjala,Yasir Jamal,Ali Faisal,Rashid Ali,Umme Rabab Syed,Raja Abbas |
| Citations | 0 |
| DOI | 10.1109/icet66147.2025.11321414 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W7123662747 |
| Type | conference-paper |
| Year | 2025 |

## Paper authors

- [Umme Rabab Syed](https://scholariq.org/researchers/umme-rabab-syed/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

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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.