# Layer-Wise External Attention by Well-Localized Attention Map for Efficient Deep Anomaly Detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/layer-wise-external-attention-by-well-localized-attention-map-for-efficient-deep/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Keiichi Nakanishi,Ryo Shiroma,Tokihisa Hayakawa,Ryoya Katafuchi,T Tokunaga |
| Citations | 3 |
| DOI | 10.1007/s42979-024-02912-3 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://link.springer.com/content/pdf/10.1007/s42979-024-02912-3.pdf |
| OpenAlex ID | https://openalex.org/W4399074880 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Ryoya Katafuchi](https://scholariq.org/researchers/ryoya-katafuchi/)

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

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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.