# Layer-wise External Attention for Efficient Deep Anomaly Detection

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/layer-wise-external-attention-for-efficient-deep-anomaly-detection/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Tokihisa Hayakawa,Keiichi Nakanishi,Ryoya Katafuchi,T Tokunaga |
| Citations | 1 |
| DOI | 10.5220/0011856800003497 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | http://dx.doi.org/10.5220/0011856800003497 |
| OpenAlex ID | https://openalex.org/W4366808987 |
| Type | conference-paper |
| Year | 2023 |

## 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/)
- [Advanced Malware Detection Techniques](https://scholariq.org/topics/advanced-malware-detection-techniques/)
- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)

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