Results 151 to 160 of about 26,456 (261)
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 +6 more
wiley +1 more source
Research on Space-Based Gravitational Wave Signal Denoising Based on Improved VMD with Parrot Algorithm. [PDF]
Xi J, Li X, Liu Y, Xu D, Shen Q, Liu H.
europepmc +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
An Adaptive Signal Denoising Method Based on Reweighted SVD for the Fault Diagnosis of Rolling Bearings. [PDF]
Wang B, Ding C.
europepmc +1 more source
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 +8 more
wiley +1 more source
A tongue‐like bioactuator is developed using orthogonally aligned cultured skeletal muscle tissues. By applying directional electrical stimulation of varying strengths, the actuator achieves jointless, multidirectional movements. The device features a fully soft, skeleton‐free design, enabling biomimetic deformation and functional actuation, and offers
Xuankai Gao +4 more
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source
From Microscale to Nanoscale Shadow Electrochemiluminescence Microscopy
In this research we report on the label‐free shadow electrochemiluminescence (shadow ECL) microscopy of microscale and nanoscale objects. By systematically investigating various influencing factors—including optical configuration, electrode activity, frame averaging, exposure time, and particle arrangement—we further confirm the nano‐imaging potential ...
Xiaodan Gou +5 more
wiley +2 more sources
Signal Denoising Method Based on EEMD and SSA Processing for MEMS Vector Hydrophones. [PDF]
Wang P, Dong J, Wang L, Qiao S.
europepmc +1 more source
ABSTRACT The rapid evolution of the Internet of Things (IoT) has significantly advanced the field of electrocardiogram (ECG) monitoring, enabling real‐time, remote, and patient‐centric cardiac care. This paper presents a comprehensive survey of AI assisted IoT‐based ECG monitoring systems, focusing on the integration of emerging technologies such as ...
Amrita Choudhury +2 more
wiley +1 more source

