# A Comparative Evaluation of Deep Learning Anomaly Detection Techniques on Semiconductor Multivariate Time Series Data

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-comparative-evaluation-of-deep-learning-anomaly-detection-techniques-on/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Philip Tchatchoua,Guillaume Graton,Mustapha Ouladsine,Michel Juge |
| Citations | 8 |
| DOI | 10.1109/case49439.2021.9551541 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3202584185 |
| Type | conference-paper |
| Year | 2021 |

## Paper authors

- [Michel Juge](https://scholariq.org/researchers/michel-juge/)

## 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/)
- [Fault Detection and Control Systems](https://scholariq.org/topics/fault-detection-and-control-systems/)
- [Currency Recognition and Detection](https://scholariq.org/topics/currency-recognition-and-detection/)

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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.