Results 211 to 220 of about 18,244,520 (347)

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

Noise2Average: An iterative residual learning strategy for image denoising without clean data. [PDF]

Imaging Neurosci (Camb)
Li Z, Li Z, Bilgic B, Ying K, Salat DH, Polimeni JR, Liao H, Huang SY, Tian Q.   +8 more
europepmc   +1 more source

SuperResNET: Model‐Free Single‐Molecule Network Analysis Software Achieves Molecular Resolution of Nup96

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
SuperResNET is a powerful integrated software that reconstructs network architecture and molecular distribution of subcellular structures from single molecule localization microscopy datasets. SuperResNET segments the nuclear pore complex and corners, extracts size, shape, and network features of all segmented nuclear pores and uses modularity analysis
Yahongyang Lydia Li, Ismail M. Khater, Christian Hallgrimson, Ben Cardoen, Timothy H. Wong, Ghassan Hamarneh, Ivan R. Nabi   +6 more
wiley   +1 more source

A shared mucosal gut microbiota signature in primary sclerosing cholangitis before and after liver transplantation

Hepatology, EarlyView., 2022
In this study of the gut mucosal microbiota in primary sclerosing cholangitis (PSC), we found consistent microbiota features associated with PSC and recurrent PSC, PSC with inflammatory bowel disease and a persistent gut dysbiosis after liver transplantation Abstract Background and Aims Several characteristic features of the fecal microbiota have been ...
Mikal Jacob Hole, Kristin Kaasen Jørgensen, Kristian Holm, Peder R. Braadland, Malin Holm Meyer‐Myklestad, Asle Wilhelm Medhus, Dag Henrik Reikvam, Alexandra Götz, Krzysztof Grzyb, Kirsten Muri Boberg, Tom Hemming Karlsen, Martin Kummen, Johannes R. Hov   +12 more
wiley   +1 more source

Comparative study of wavelet transform and Fourier domain filtering for medical image denoising. [PDF]

Sci Rep
Saif MA, Mughalles BM, Loqman IGH.
europepmc   +1 more source

Robust Representation Learning for Clean Feature Discovery in Incomplete Multi‐View Clustering

Advanced Intelligent Systems, EarlyView.
Robust feature discovery in incomplete multi‐view clustering is achieved by coupling RPCA‐based clean representation recovery with neural‐network‐assisted graph learning. The resulting RIMVC framework constructs cleaner and more discriminative graph‐structured representations from incomplete and noisy multi‐view data, improving clustering robustness ...
Ping Hu, Chenggang Lu, Rui Zhang, Haijun Yan, Yesong Xu   +4 more
wiley   +1 more source

Enhanced color image denoising using fuzzy metric-like space and peer group. [PDF]

Sci Rep
Rashid M, Ali F, Batool N, Azam A.
europepmc   +1 more source

Digital Twins for the Design, Interactive Control, and Deployment of Modular, Fiber‐Reinforced Soft Continuum Arms

Advanced Intelligent Systems, EarlyView.
A digital twin framework is presented for modular soft continuum arms built from fiber‐reinforced pneumatic actuators. Cosserat rod models describe individual actuators, while virtual assemblies are formed through serial and parallel networks, preserving actuator‐level architecture and arm deformation.
Seung Hyun Kim, Jiamiao Guo, Arman Tekinalp, Heng‐Sheng Chang, Ugur Akcal, Tixian Wang, Darren Biskup, Benjamin Walt, Girish Chowdhary, Girish Krishnan, Prashant G. Mehta, Mattia Gazzola   +11 more
wiley   +1 more source

Multiobjective framework for hardware and quality aware approximate Gaussian filtering toward energy efficient ultrasound image denoising. [PDF]

Sci Rep
Sana S, Shaukat A, Khawaja SG, Qahmash A.   +3 more
europepmc   +1 more source

A NEAT Approach to Evolving Neural‐Network‐Based Optimization of Chiral Photonic Metasurfaces: Application of a NeuroEvolution‐of‐Augmenting‐Topologies Pipeline

Advanced Intelligent Systems, EarlyView.
Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley   +1 more source