# A spatio-temporal anomaly detection system to support understanding of abnormal phenomena in automated manufacturing lines

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/a-spatio-temporal-anomaly-detection-system-to-support-understanding-of-abnormal/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Sho Okazaki,Kohei Kaminishi,Yusheng Wang,Takuma Fujiu,Yuji Nakata,S. Hamamoto,Kenshin Yokose,Tatsunori Hara,Yasushi Umeda,Jun Ota |
| Citations | 0 |
| DOI | 10.1016/j.compind.2026.104481 |
| Fields | Engineering |
| Open Access | true |
| OA Status | hybrid |
| OA URL | https://doi.org/10.1016/j.compind.2026.104481 |
| OpenAlex ID | https://openalex.org/W4411387603 |
| Type | article |
| Year | 2026 |

## Paper authors

- [Sho Okazaki](https://scholariq.org/researchers/sho-okazaki/)

## Paper journal

- [Computers in Industry](https://scholariq.org/journals/computers-in-industry/)

## Paper primary topic

- [Industrial Vision Systems and Defect Detection](https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/)

## Paper topics

- [Industrial Vision Systems and Defect Detection](https://scholariq.org/topics/industrial-vision-systems-and-defect-detection/)
- [Fault Detection and Control Systems](https://scholariq.org/topics/fault-detection-and-control-systems/)
- [Digital Transformation in Industry](https://scholariq.org/topics/digital-transformation-in-industry/)

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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.