Cargando…
A comparison of deep-learning-based inpainting techniques for experimental X-ray scattering
The implementation is proposed of image inpainting techniques for the reconstruction of gaps in experimental X-ray scattering data. The proposed methods use deep learning neural network architectures, such as convolutional autoencoders, tunable U-Nets, partial convolution neural networks and mixed-s...
| Autores principales: | , , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
International Union of Crystallography
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533742/ https://www.ncbi.nlm.nih.gov/pubmed/36249508 http://dx.doi.org/10.1107/S1600576722007105 |