# Advancements in Data Augmentation and Transfer Learning:A Comprehensive Survey to Address Data Scarcity Challenges

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/advancements-in-data-augmentation-and-transfer-learning-a-comprehensive-survey/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Salma Fayaz,Syed Zubair Ahmad Shah,Nusrat Mohi Ud Din,Naillah Gul,Assif Assad |
| Citations | 33 |
| DOI | 10.2174/0126662558286875231215054324 |
| Fields | Computer Science,Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4390742397 |
| Type | article |
| Year | 2024 |

## Paper authors

- [Assif Assad](https://scholariq.org/researchers/assif-assad/)

## Paper journal

- [Recent Advances in Computer Science and Communications](https://scholariq.org/journals/recent-advances-in-computer-science-and-communications/)

## Paper primary topic

- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)

## Paper topics

- [Adversarial Robustness in Machine Learning](https://scholariq.org/topics/adversarial-robustness-in-machine-learning/)
- [Anomaly Detection Techniques and Applications](https://scholariq.org/topics/anomaly-detection-techniques-and-applications/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)

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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.