# Semantic Segmentation using Vision Transformers: A survey

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/semantic-segmentation-using-vision-transformers-a-survey/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Hans Thisanke,Chamli Deshan,Kavindu Chamith,Sachith Seneviratne,Rajith Vidanaarachchi,Damayanthi Herath |
| Citations | 15 |
| DOI | 10.48550/arxiv.2305.03273 |
| Fields | Computer Science,Medicine |
| Open Access | true |
| OA Status | green |
| OA URL | https://arxiv.org/pdf/2305.03273 |
| OpenAlex ID | https://openalex.org/W4376865103 |
| Type | preprint |
| Year | 2023 |

## Paper authors

- [Damayanthi Herath](https://scholariq.org/researchers/damayanthi-herath/)

## Paper journal

- [arXiv (Cornell University)](https://scholariq.org/journals/arxiv-cornell-university/)

## Paper primary topic

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)

## Paper topics

- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [COVID-19 diagnosis using AI](https://scholariq.org/topics/covid-19-diagnosis-using-ai/)
- [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.