Results 201 to 210 of about 26,456 (261)

Deep learning‐driven methods for fluorescence imaging denoising

Interdisciplinary Medicine, EarlyView.
This review evaluates data‐driven deep learning denoising methods that overcome conventional limitations through effective feature extraction and nonlinear modeling. Focusing on fluorescence imaging acquisition under photon‐limited conditions, we delineate cutting‐edge architectures, including supervised learning, unsupervised learning, zero‐shot ...
Xinyu Lu, Zixu Zhan, Bin Tan, Ruiwen Wang, Shuyue Wang, Diming Zhang, Bobo Cai, Zhijing Zhu   +7 more
wiley   +1 more source

Linear anti-jamming algorithm design for multi-channel optical fiber communication. [PDF]

PLoS One
Yu H.
europepmc   +1 more source

Deep Learning Integration in Optical Microscopy: Advancements and Applications

Microscopy Research and Technique, EarlyView.
It explores the integration of DL into optical microscopy, focusing on key applications including image classification, segmentation, and computational reconstruction. ABSTRACT Optical microscopy is a cornerstone imaging technique in biomedical research, enabling visualization of subcellular structures beyond the resolution limit of the human eye ...
Pottumarthy Venkata Lahari, Sagnika Dutta, H. Deeksha, Samreen A. Patel, Budheswar Dehury, Nirmal Mazumder   +5 more
wiley   +1 more source

A high-performance training-free pipeline for robust random telegraph signal characterization via adaptive wavelet-based denoising and Bayesian digitization methods. [PDF]

Sci Rep
Bai T, Kapoor A, Kim NY.
europepmc   +1 more source

Impact of thermal and physiological denoising on laminar functional connectivity. [PDF]

Sci Rep
Guidi M, Giulietti G, Sharoh D, Markuerkiaga I, Knudsen L, Poser BA, Huber L, Möller HE, Norris DG, Giove F.   +9 more
europepmc   +1 more source