# On Evaluating Black-Box Explainable AI Methods for Enhancing Anomaly Detection in Autonomous Driving Systems

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/on-evaluating-black-box-explainable-ai-methods-for-enhancing-anomaly-detection/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sazid Nazat,Osvaldo Arreche,Mustafa Abdallah |
| Citations | 35 |
| DOI | 10.3390/s24113515 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/1424-8220/24/11/3515/pdf?version=1716996992 |
| OpenAlex ID | https://openalex.org/W4399181715 |
| PMID | 38894306 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Mustafa Abdallah](https://scholariq.org/researchers/mustafa-abdallah/)

## Paper journal

- [Sensors](https://scholariq.org/journals/sensors/)

## 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/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Explainable Artificial Intelligence (XAI)](https://scholariq.org/topics/explainable-artificial-intelligence-xai/)

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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.