Results 231 to 240 of about 344,629 (305)

Enhancing Atomic‐Resolution in Electron Microscopy: A Deep Learning Denoiser Operating in the Frequency Domain

Advanced Intelligent Systems, EarlyView.
The newly developed AI‐automated Fast Fourier Transform denoising algorithm surpasses conventional real‐space methods by revealing even light atoms otherwise hidden in noisy backgrounds. Atomic resolution electron microscopy has become an essential tool for many scientific fields, when direct visualization of atomic arrangements and defects is needed ...
Ivan Pinto‐Huguet, Marc Botifoll, Xuli Chen, Martin Børstad Eriksen, Jing Yu, Giovanni Isella, Andreu Cabot, Gonzalo Merino, Jordi Arbiol   +8 more
wiley   +1 more source

A Language model-based approach to sentiment classification of languages in central Asia. [PDF]

Sci Rep
Muhetaer P, Wenqiang G, Chong L.
europepmc   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

Data-driven ANN-based visual decoding enables unsupervised functional alignment. [PDF]

Commun Biol
Zhang XY, Lin H, Deng Z, Siegel M, Miller EK, Yan G.   +5 more
europepmc   +1 more source

Explainable AI‐Driven Optimization of Electrode Activation Reduces Power Consumption While Preserving Object Recognition in Retinal Prostheses

Advanced Intelligent Systems, EarlyView.
Explainable artificial intelligence (XAI) guides selective electrode activation in retinal prostheses by emphasizing visually informative regions. XAI‐assisted phosphene generation maintains object recognition performance while significantly reducing stimulation power.
Sein Kim, Hamin Shim, Maesoon Im
wiley   +1 more source

Dynamic supply-side multipliers in China's marine economy: A neural network-enhanced Ghosh model for sustainable development. [PDF]

PLoS One
Jin J, Zhang M.
europepmc   +1 more source

Xstainer: A Novel Virtual Staining Tool Powered by Advanced Deep Learning Techniques

Advanced Intelligent Systems, EarlyView.
Xstainer is a deep learning–based virtual staining framework that converts hematoxylin and eosin‐stained whole slide images into multiple histochemical stains, including Masson's trichrome, Periodic acid‐Schiff, Jones methenamine silver, and Toluidine blue.
Fatma Nur Kinali, Derya Demir, Kutsev B. Ozyoruk, Yasin Almalioglu, Emre C. Kose, Drew F. K. Williamson, Gurdeniz Serin, G. Evren Keles, Banu S. Kumbaraci, Ceren Utku, Uguray P. Hacisalihoglu, Ilknur Turkmen, Figen Ozturk, Kayhan Basak, Yavuz Nuri Ertas, Mehmet Turan   +15 more
wiley   +1 more source

Machine learning-based method for determining regional parameters of the HSS model: a case study of Qingdao, China. [PDF]

Sci Rep
Yuan C, Zhang Q, Feng H, Wang K, Zhang S.   +4 more
europepmc   +1 more source

An Integrated and Robust Deep Learning Framework for Denoising and Analyzing Single‐Cell Spatial Transcriptomics

Advanced Intelligent Systems, EarlyView.
Single‐cell Spatial Transcriptomics Analysis and Denoising Engine is introduced as a unified deep learning framework that jointly performs denoising, clustering, and gene prioritization in spatial transcriptomics. By integrating linear and nonlinear representations within a dual‐channel architecture, it improves robustness and accuracy, uncovers ...
Yaxuan Cui, Yang Cui, Ruheng Wang, Xin Zeng, Zheyong Zhu, Ding Yi, Ruihua Guo, Tetsuya Sakurai, Kenta Nakai, Xiucai Ye, Leyi Wei, Yong Chen   +11 more
wiley   +1 more source

Quantifying erosion-induced carbon emissions from SOC decomposition across sediment pathways in the yellow river basin. [PDF]

Carbon Balance Manag
Guo J, Yang Y, Soothar MK, Qi Y.
europepmc   +1 more source