# Hand Gesture Recognition as Signal for Help using Deep Neural Network

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/hand-gesture-recognition-as-signal-for-help-using-deep-neural-network/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Nathasia Florentina Thejowahyono,Michael Vincentius Setiawan,Seto Benson Handoyo,Abdul Haris Rangkuti |
| Citations | 6 |
| DOI | 10.46338/ijetae0222_05 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | bronze |
| OA URL | https://doi.org/10.46338/ijetae0222_05 |
| OpenAlex ID | https://openalex.org/W4210741816 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Abdul Haris Rangkuti](https://scholariq.org/researchers/abdul-haris-rangkuti/)

## Paper journal

- [International Journal of Emerging Technology and Advanced Engineering](https://scholariq.org/journals/international-journal-of-emerging-technology-and-advanced-engineering/)

## Paper primary topic

- [Hand Gesture Recognition Systems](https://scholariq.org/topics/hand-gesture-recognition-systems/)

## Paper topics

- [Hand Gesture Recognition Systems](https://scholariq.org/topics/hand-gesture-recognition-systems/)
- [Edcuational Technology Systems](https://scholariq.org/topics/edcuational-technology-systems/)

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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.