Three-dimensional nanoscale reduced-angle ptycho-tomographic imaging with deep learning (RAPID)
X-ray ptychographic tomography is a nondestructive method for three dimensional (3D)
imaging with nanometer-sized resolvable features. The size of the volume that can be …
imaging with nanometer-sized resolvable features. The size of the volume that can be …
An efficient ptychography reconstruction strategy through fine-tuning of large pre-trained deep learning model
X Pan, S Wang, Z Zhou, L Zhou, P Liu, C Li, W Wang… - Iscience, 2023 - cell.com
With pre-trained large models and their associated fine-tuning paradigms being constantly
applied in deep learning, the performance of large models achieves a dramatic boost …
applied in deep learning, the performance of large models achieves a dramatic boost …
Randomized algorithms for scientific computing (RASC)
Randomized algorithms have propelled advances in artificial intelligence and represent a
foundational research area in advancing AI for Science. Future advancements in DOE Office …
foundational research area in advancing AI for Science. Future advancements in DOE Office …
Compressive ptychography using deep image and generative priors
Ptychography is a well-established coherent diffraction imaging technique that enables non-
invasive imaging of samples at a nanometer scale. It has been extensively used in various …
invasive imaging of samples at a nanometer scale. It has been extensively used in various …
A Deep Generative Approach to Oversampling in Ptychography
Ptychography is a well-studied phase imaging method that makes non-invasive imaging
possible at a nanometer scale. It has developed into a mainstream technique with various …
possible at a nanometer scale. It has developed into a mainstream technique with various …
[PDF][PDF] An efficient ptychography reconstruction strategy through fine-tuning of large pre-trained deep learning model
Z Zhou, Y Zhang, YZ Dong - researchgate.net
With pre-trained large models and their associated fine-tuning paradigms being constantly
applied in deep learning, the performance of large models achieves a dramatic boost …
applied in deep learning, the performance of large models achieves a dramatic boost …