Results 111 to 120 of about 114,074 (272)

Minimizing the distortions in electrophysiological source imaging of cortical oscillatory activity via Spectral Structured Sparse Bayesian Learning. [PDF]

Front Neurosci, 2023
Paz-Linares D, Gonzalez-Moreira E, Areces-Gonzalez A, Wang Y, Li M, Vega-Hernandez M, Wang Q, Bosch-Bayard J, Bringas-Vega ML, Martinez-Montes E, Valdes-Sosa MJ, Valdes-Sosa PA.   +11 more
europepmc   +1 more source

Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy

Advanced Intelligent Systems, EarlyView.
Hallgrimson et al. introduce a machine learning algorithm, siMILe, that takes features of single‐molecule localization microscopy localization clusters (e.g., size and sphericity) and finds the clusters that are associated with certain cell conditions (such as differential protein expression or drug treatment).
Christian Hallgrimson, Y. Lydia Li, Claire A. Shou, Ben Cardoen, John Lim, Timothy H. Wong, Ismail M. Khater, Ivan Robert Nabi, Ghassan Hamarneh   +8 more
wiley   +1 more source

DOA Estimation for Massive MIMO Systems with Unknown Mutual Coupling Based on Block Sparse Bayesian Learning. [PDF]

Sensors (Basel), 2022
Liu Y, Dong N, Zhang X, Zhao X, Zhang Y, Qiu T.   +5 more
europepmc   +1 more source

i‐Tac: Inverse Design of 3D‐Printed Tactile Elastomers with Tuneable Optical and Mechanical Properties

Advanced Intelligent Systems, EarlyView.
Inspired by the multi‐tissue architecture of the human fingertip dermis (A), this work introduces a mixture design using three PolyJet materials (AC/TM/GM) to expand the achievable elastomer property space (B). An inverse design pipeline (i‐Tac) is developed to map target optical/mechanical requirements to optimal material compositions (C), enabling ...
Wen Fan, Dandan Zhang
wiley   +1 more source

Improved Variational Bayes for Space-Time Adaptive Processing

Entropy
To tackle the challenge of enhancing moving target detection performance in environments characterized by small sample sizes and non-uniformity, methods rooted in sparse signal reconstruction have been incorporated into Space-Time Adaptive Processing ...
Kun Li, Jinyang Luo, Peng Li, Guisheng Liao, Zhixiang Huang, Lixia Yang   +5 more
doaj   +1 more source

A Space-Time Adaptive Processing Method Based on Sparse Bayesian Learning for Maneuvering Airborne Radar. [PDF]

Sensors (Basel), 2022
Zhang S, Wang T, Liu C, Wang D.
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

Off-Grid DOA Estimation Using Sparse Bayesian Learning for MIMO Radar under Impulsive Noise. [PDF]

Sensors (Basel), 2022
Ma J, Zhang J, Yang Z, Qiu T.
europepmc   +1 more source

Disentangling Aleatoric and Epistemic Uncertainty in Physics‐Informed Neural Networks: Application to Insulation Material Degradation Prognostics

Advanced Intelligent Systems, EarlyView.
Physics‐Informed Neural Networks (PINNs) provide a framework for integrating physical laws with data. However, their application to Prognostics and Health Management (PHM) remains constrained by the limited uncertainty quantification (UQ) capabilities.
Ibai Ramirez, Jokin Alcibar, Joel Pino, Mikel Sanz, Jose I. Aizpurua   +4 more
wiley   +1 more source

Experimental Validation of Entropy-Driven Swarm Exploration under Sparsity Constraints with Sparse Bayesian Learning. [PDF]

Entropy (Basel), 2022
Manss C, Kuehner I, Shutin D.
europepmc   +1 more source