# Cross-Modality Image Synthesis from Unpaired Data Using CycleGAN

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/cross-modality-image-synthesis-from-unpaired-data-using-cyclegan/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yuta Hiasa,Yoshito Otake,Masaki Takao,Takumi Matsuoka,Kazuma Takashima,Aaron Carass,Jerry L. Prince,Nobuhiko Sugano,Yoshinobu Sato |
| Citations | 196 |
| DOI | 10.1007/978-3-030-00536-8_4 |
| Fields | Computer Science |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W2962784654 |
| Type | conference-paper |
| Year | 2018 |

## Paper authors

- [Masaki Takao](https://scholariq.org/researchers/masaki-takao/)

## Paper journal

- [Lecture notes in computer science](https://scholariq.org/journals/lecture-notes-in-computer-science/)

## Paper primary topic

- [Generative Adversarial Networks and Image Synthesis](https://scholariq.org/topics/generative-adversarial-networks-and-image-synthesis/)

## Paper topics

- [Generative Adversarial Networks and Image Synthesis](https://scholariq.org/topics/generative-adversarial-networks-and-image-synthesis/)
- [Advanced Neural Network Applications](https://scholariq.org/topics/advanced-neural-network-applications/)
- [Computer Graphics and Visualization Techniques](https://scholariq.org/topics/computer-graphics-and-visualization-techniques/)

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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.