Results 111 to 120 of about 83,179 (266)
Machine‐Learning‐Assisted Onset‐Time Determination in Transient Luminescence Thermometry
Artificial neural networks enable autonomous extraction of onset times from transient heating curves in luminescence thermometry. Using Ln3+‐doped upconverting nanoparticles as luminescent thermometers, we combine experimental transients with physically motivated synthetic curves to enhance data diversity and improve generalization.
David J. Sousa +3 more
wiley +1 more source
Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang +9 more
wiley +1 more source
A Critical Assessment of Bonding Descriptors for Predicting Materials Properties
The impact of new bonding descriptors in machine learning models for predicting material properties is assessed. Improvements are validated using significance tests, and new, intuitive descriptors for screening lattice thermal conductivity and projected force constants are introduced.
Aakash Ashok Naik +6 more
wiley +1 more source
Calibration‐Free Electromyography Motor Intent Decoding Using Large‐Scale Supervised Pretraining
Calibration‐free electromyography motor intent decoding is enabled through large‐scale supervised pretraining across heterogeneous datasets. A Spatially Aware Feature‐learning Transformer processes variable channel counts and electrode geometries, allowing transfer across users and recording setups. On a held‐out benchmark, fine‐tuned cross‐user models
Alexander E. Olsson +3 more
wiley +1 more source
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 +6 more
wiley +1 more source
This paper presents a high‐speed object pose estimation method that deconstructs objects into geometric components. Inspired by human cognitive generalization, it detects these primitives and infers the 6D pose from their stable spatial configuration.
Xuyang Li +6 more
wiley +1 more source
Correction: Rare event detection by progressive clustering undersampling. [PDF]
PLOS One Staff.
europepmc +1 more source
Neuromorphic Denoising with Fully Analog Memristive In‐Memory Computing
This article borrows the concepts of episodic memory in human brains to experimentally implement a memristor‐based neuromorphic denoising process. A homogeneous memristor processing unit is experimentally demonstrated for both temporal storage and neural network computation, imitating the synapses in the human brain.
Daijing Shi +5 more
wiley +1 more source
Steering Langevin Dynamics toward Transition States Using Collective-Variable-Free Resampling. [PDF]
Ketter M, Madsen GKH.
europepmc +1 more source
Scene‐Customized Learning for Multi‐Depth 3D Phase‐Only Hologram Generation
Scene‐customized geometric modeling constructs GM‐4K, a controllable 4K RGB‐D dataset for learning‐based multi‐depth hologram generation. By tuning intensity spectra and depth‐region sampling, the dataset reveals how training‐data statistics affect phase‐only hologram encoding and supports a spectral test framework for evaluating model generalization ...
Yanan Zhang +5 more
wiley +1 more source

