A 3D reconstruction based on an unsupervised domain adaptive for binocular endoscopy

In minimally invasive surgery, endoscopic image quality plays a crucial role in surgery. Aiming at the lack of a real parallax in binocular endoscopic images, this article proposes an unsupervised adaptive neural network. The network combines adaptive smoke removal, depth estimation of binocular end...

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Detalles Bibliográficos
Autores principales: Zhang, Guo, Huang, Zhiwei, Lin, Jinzhao, Li, Zhangyong, Cao, Enling, Pang, Yu, sun, Weiwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Physiology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9475117/
https://www.ncbi.nlm.nih.gov/pubmed/36117683
http://dx.doi.org/10.3389/fphys.2022.994343

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9475117/
https://www.ncbi.nlm.nih.gov/pubmed/36117683
http://dx.doi.org/10.3389/fphys.2022.994343

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