# GLoRIA: A Multimodal Global-Local Representation Learning Framework for Label-efficient Medical Image Recognition

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/gloria-a-multimodal-global-local-representation-learning-framework-for-label/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Shih-Cheng Huang,Liyue Shen,Matthew P. Lungren,Serena Yeung |
| Citations | 407 |
| DOI | 10.1109/iccv48922.2021.00391 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3201906559 |
| Type | conference-paper |
| Year | 2021 |

## Paper authors

- [Serena Yeung](https://scholariq.org/researchers/serena-yeung/)

## Paper primary topic

- [Multimodal Machine Learning Applications](https://scholariq.org/topics/multimodal-machine-learning-applications/)

## Paper topics

- [Multimodal Machine Learning Applications](https://scholariq.org/topics/multimodal-machine-learning-applications/)
- [Topic Modeling](https://scholariq.org/topics/topic-modeling/)
- [Domain Adaptation and Few-Shot Learning](https://scholariq.org/topics/domain-adaptation-and-few-shot-learning/)

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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.