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The challenge of imaging low-density objects in an electron microscope without causing beam damage is significant in modern TEM. This is especially true for life science imaging, where the sample, rather than the instrument, still…

Optics · Physics 2025-01-29 Francisco Vega Ibáñez , Jo Verbeeck

Single particle diffraction imaging experiments at free-electron lasers (FEL) have a great potential for structure determination of reproducible biological specimens that can not be crystallized. One of the challenges in processing the data…

Biological Physics · Physics 2013-10-16 O. M. Yefanov , I. A. Vartanyants

Mechanical shear deformations lead, in some cases, to effects similar to those resulting from ion irradiation. Here we characterize the effects of shear velocity and temperature on amorphous silicon (\aSi) modelled using classical molecular…

Materials Science · Physics 2015-05-19 Ali Kerrache , Normand Mousseau , Laurent J. Lewis

We propose a novel approach to model amorphous materials using a first principles density functional method while simultaneously enforcing agreement with selected experimental data. We illustrate our method with applications to amorphous…

Materials Science · Physics 2009-11-10 Parthapratim Biswas , De Nyago Tafen , Raymond Atta-Fynn , D. A. Drabold

AMORPH utilizes a new Bayesian statistical approach to interpreting X-ray diffraction results of samples with both crystalline and amorphous components. AMORPH fits X-ray diffraction patterns with a mixture of narrow and wide components,…

Data Analysis, Statistics and Probability · Physics 2018-08-15 Michael C. Rowe , Brendon J. Brewer

The rapid advancement of generative image models has transformed digital media to the point where AI generated images can no longer be reliably distinguished from authentic photographs by human observers or many conventional detection…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Mohd Ruhul Ameen , Akif Islam

Incorporating diffusion models in the image compression domain has the potential to produce realistic and detailed reconstructions, especially at extremely low bitrates. Previous methods focus on using diffusion models as expressive…

Image and Video Processing · Electrical Eng. & Systems 2024-10-10 Lucas Relic , Roberto Azevedo , Markus Gross , Christopher Schroers

We provide a framework for solving inverse problems with diffusion models learned from linearly corrupted data. Firstly, we extend the Ambient Diffusion framework to enable training directly from measurements corrupted in the Fourier…

Computer Vision and Pattern Recognition · Computer Science 2025-04-23 Asad Aali , Giannis Daras , Brett Levac , Sidharth Kumar , Alexandros G. Dimakis , Jonathan I. Tamir

Optical aberrations prevent telescopes from reaching their theoretical diffraction limit. Once estimated, these aberrations can be compensated for using deformable mirrors in a closed loop. Focal plane wavefront sensing enables the…

Refraction of an optical probe beam by a plasma can be measured with angular filter refractometry (AFR), which produces an image containing intensity contours that correspond to curves of constant refraction angle. Further analysis is…

Real-image super-resolution (Real-ISR) seeks to recover HR images from LR inputs with mixed, unknown degradations. While diffusion models surpass GANs in perceptual quality, they under-reconstruct high-frequency (HF) details due to a…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Seungho Choi , Jeahun Sung , Jihyong Oh

Imaging inverse problems can be solved in an unsupervised manner using pre-trained diffusion models, but doing so requires approximating the gradient of the measurement-conditional score function in the diffusion reverse process. We show…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Matt C. Bendel , Saurav K. Shastri , Rizwan Ahmad , Philip Schniter

We present an information-based total-energy optimization method to produce nearly defect-free structural models of amorphous silicon. Using geometrical, structural and topological information from disordered tetrahedral networks, we have…

Disordered Systems and Neural Networks · Physics 2019-01-28 Dil K. Limbu , Raymond Atta-Fynn , Parthapratim Biswas

Generating large-scale, physically consistent AC Optimal Power Flow (ACOPF) datasets is essential for modern data-driven power system applications. The central challenge lies in balancing solution accuracy with computational efficiency.…

Systems and Control · Electrical Eng. & Systems 2026-02-04 Shashank Shekhar , Abhinav Karn , Kris Keshav , Shivam Bansal , Parikshit Pareek

Face recognition systems have become increasingly vulnerable to security threats in recent years, prompting the use of Face Anti-spoofing (FAS) to protect against various types of attacks, such as phone unlocking, face payment, and…

Computer Vision and Pattern Recognition · Computer Science 2023-09-19 Mouxiao Huang

Determining atomistic structures from characterization data is one of the most common yet intricate problems in materials science. Particularly in amorphous materials, proposing structures that balance realism and agreement with experiments…

Disordered Systems and Neural Networks · Physics 2026-03-25 Jiawei Guo , Daniel Schwalbe-Koda

We present new atomistic models of amorphous silicon (a-Si) and hydrogenated amorphous silicon (a-Si:H) surfaces. The a-Si model included 4096 atoms and was obtained using local orbital density functional theory. By analyzing a slab model…

Materials Science · Physics 2025-06-24 Kishor Nepal , Aashish Gautam , Chinonso Ugwumadu , David Drabold

We present results from the SPring-8 Angstrom Compact free electron LAser (SACLA) XFEL facility, using a high intensity ($\sim\!10^{20}\,$W/cm$^2$) X-ray pump X-ray probe scheme to observe changes in the ionic structure of silicon induced…

Recent advances in diffusion models have enabled the creation of deceptively real images, posing significant security risks when misused. In this study, we empirically show that different timesteps of DDIM inversion reveal varying subtle…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Yixin Wu , Feiran Zhang , Tianyuan Shi , Ruicheng Yin , Zhenghua Wang , Zhenliang Gan , Xiaohua Wang , Changze Lv , Xiaoqing Zheng , Xuanjing Huang

Diffusion-based super-resolution (SR) models have recently garnered significant attention due to their potent restoration capabilities. But conventional diffusion models perform noise sampling from a single distribution, constraining their…

Computer Vision and Pattern Recognition · Computer Science 2025-02-13 Chengcheng Wang , Zhiwei Hao , Yehui Tang , Jianyuan Guo , Yujie Yang , Kai Han , Yunhe Wang