# Feature Correlated Auto Encoder Method for Industrial 4.0 Process Inspection Using Computer Vision and Machine Learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/feature-correlated-auto-encoder-method-for-industrial-4-0-process-inspection/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Pradeep Bedi,S. B. Goyal,Anand Singh Rajawat,Pawan Bhaladhare,Alok Aggarwal,Ajay Prasad |
| Citations | 7 |
| DOI | 10.1016/j.procs.2023.01.059 |
| Fields | Engineering |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://doi.org/10.1016/j.procs.2023.01.059 |
| OpenAlex ID | https://openalex.org/W4318570562 |
| Type | conference-paper |
| Year | 2023 |

## Paper authors

- [Pawan Bhaladhare](https://scholariq.org/researchers/pawan-bhaladhare/)

## Paper journal

- [Procedia Computer Science](https://scholariq.org/journals/procedia-computer-science/)

## 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/)
- [Digital Transformation in Industry](https://scholariq.org/topics/digital-transformation-in-industry/)
- [Manufacturing Process and Optimization](https://scholariq.org/topics/manufacturing-process-and-optimization/)

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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.