Advanced Science, EarlyView.This study systematically reveals a complex interactive network involving plants, microbes, and insects, elucidating the ecological and molecular mechanisms by which cotton enhances its resistance to aphids through the active recruitment of the beneficial soil bacterium Delftia tsuruhatensis.
Hui Xue +11 more
wiley +1 more source
Vibration Signal Denoising Method Based on ICFO-SVMD and Improved Wavelet Thresholding. [PDF]
Sensors (Basel)Cui Y, He X, Wu Z, Zhang Q, Cao Y.
europepmc +1 more source
Real-Time Fast Fourier Transform-Based Notch Filter for Single-Frequency Noise Cancellation: Application to Electrocardiogram Signal Denoising. [PDF]
J Med Signals Sens, 2021 Slimane AB, Zaid AO.
europepmc +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
PDRNet: A Novel Physical Feature-Driven Residual Network for Motor Vibration Signal Denoising. [PDF]
Sensors (Basel)Yu K, Wu X, Yang M, Lin F, Liang Z.
europepmc +1 more source
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
LRR-UNet: A Deep Unfolding Network With Low-Rank Recovery for EEG Signal Denoising. [PDF]
CNS Neurosci TherYue X, Lu L, Liu H, Zang Y.
europepmc +1 more source
Evolutionary multifractal signal/image denoising
, 2007 This chapter investigates the use of Evolutionary techniques for multifractal signal/image denoising. Two strategies are considered: using evolution as a pure stochastic optimiser, or using interactive evolution for a meta-optimisation task. Both strategies are complementary as they allow to address dierent aspects of signal/image denoising.
Lutton, Evelyne, Lévy Véhel, Jacques
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
Comparative evaluation of filtration techniques for ECG signal denoising with emphasis on stationary wavelet transform. [PDF]
Sci RepÁdám N +4 more
europepmc +1 more source