Results 71 to 80 of about 12,640,042 (291)
Approximate‐Guided Representation Learning in Vision Transformer
CAAI Transactions on Intelligence TechnologyIn recent years, the transformer model has demonstrated excellent performance in computer vision (CV) applications. The key lies in its guided representation attention mechanism, which uses dot‐product to depict complex feature relationships, and ...
Kaili Wang +4 more
doaj +1 more source
Interpreting uninterpretable predictors: kernel methods, Shtarkov solutions, and random forests
Statistical Theory and Related Fields, 2022 Many of the best predictors for complex problems are typically regarded as hard to interpret physically. These include kernel methods, Shtarkov solutions, and random forests.
T. M. Le, Bertrand Clarke
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Advanced Engineering Materials, EarlyView.Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn +5 more
wiley +1 more source
Pattern recognition and machine learning for magnetic resonance images with kernel methods [PDF]
, 2009 The aim of this thesis is to apply a particular category of machine learning and pattern recognition algorithms, namely the kernel methods, to both functional and anatomical magnetic resonance images (MRI). This work specifically focused on supervised
Chu, C.-Y.C.
core
New bandwidth selection for kernel quantile estimators [PDF]
, 2012 Copyright © 2012 Ali Al-Kenani and Keming Yu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly ...
Al-Kenani, A +3 more
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Kernel methods for fmri pattern prediction
, 2008 In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artifacts, spatial smoothing, removing low frequency drifts and applying multivariate ...
Saunders, Craig +3 more
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Operating System’s Kernel Hooking Methods (Study Case of Linux Kernel)
Безопасность информационных технологий, 2014 The article presents an overview of dynamic integration in the kernel Linux, allowed to modify (add, change) its functionality. Traditional methods of integration based on changing in the kernel code (patching), and methods based on using system ...
Ilya Vladimirovich Matveychikov
doaj
Supervised Kernel Principal Component Analysis by Most Expressive Feature Reordering
Journal of Telecommunications and Information Technology, 2015 The presented paper is concerned with feature space derivation through feature selection. The selection is performed on results of kernel Principal Component Analysis (kPCA) of input data samples.
Krzysztof Ślot +3 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji +3 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani +7 more
wiley +1 more source