# Convolutional Neural Networks for Automatic Virtual Metrology

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/convolutional-neural-networks-for-automatic-virtual-metrology/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yu‐Ming Hsieh,Tan-Ju Wang,Chin‐Yi Lin,Li-Hsuan Peng,Fan‐Tien Cheng,Suiyan Shang |
| Citations | 21 |
| DOI | 10.1109/lra.2021.3084882 |
| Fields | Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3176729219 |
| Type | article |
| Year | 2021 |

## Paper authors

- [Chin‐Yi Lin](https://scholariq.org/researchers/chin-yi-lin/)

## Paper journal

- [IEEE Robotics and Automation Letters](https://scholariq.org/journals/ieee-robotics-and-automation-letters/)

## 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/)
- [Surface Roughness and Optical Measurements](https://scholariq.org/topics/surface-roughness-and-optical-measurements/)
- [Image Processing Techniques and Applications](https://scholariq.org/topics/image-processing-techniques-and-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.