Results 51 to 60 of about 1,165,616 (316)

Mixture of Kernels and Iterated Semidirect Product of Diffeomorphisms Groups

, 2011
In the framework of large deformation diffeomorphic metric mapping (LDDMM), we develop a multi-scale theory for the diffeomorphism group based on previous works. The purpose of the paper is (1) to develop in details a variational approach for multi-scale
Dupuis P., François-Xavier Vialard, Grenander U., Kloft M., Laurent Risser, Martins Bruveris, Risser L., Singh N., Sommer S., Vialard F.-X.   +9 more
core   +4 more sources

Directional Global Three-part Image Decomposition

, 2015
We consider the task of image decomposition and we introduce a new model coined directional global three-part decomposition (DG3PD) for solving it. As key ingredients of the DG3PD model, we introduce a discrete multi-directional total variation norm and ...
Gottschlich, Carsten, Thai, Duy Hoang
core   +1 more source

Atrial Fibrillation Detection Using an Improved Multi-Scale Decomposition Enhanced Residual Convolutional Neural Network

IEEE Access, 2019
Atrial fibrillation, the most common sustained arrhythmia, is still a big challenge for researchers in the medical field. Many studies attempt to realize intelligent classification of AF based on deep learning methods.
Xincheng Cao, Bin Yao, Binqiang Chen
semanticscholar   +1 more source

Degradation feature extraction of the hydraulic pump based on local characteristic-scale decomposition and multi-fractal spectrum

Advances in Mechanical Engineering, 2016
Aiming at the characteristic that the vibration signals of hydraulic pump usually have strong nonlinearity and low signal-to-noise ratio, this article presents a novel hydraulic pump degradation feature extraction method based on improved local ...
Zaike Tian, Hongru Li, Jian Sun, Yifan Li   +3 more
doaj   +1 more source

A Redesigned Benders Decomposition Approach for Large-Scale In-Transit Freight Consolidation Operations

, 2018
The growth in online shopping and third party logistics has caused a revival of interest in finding optimal solutions to the large scale in-transit freight consolidation problem.
Abril, Luis E., Erkoc, Murat, Hanbazazah, Abdulkader S, Shaikh, Nazrul I   +3 more
core   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

An algorithm for the high-energy expansion of multi-loop diagrams to next-to-leading logarithmic accuracy [PDF]

, 2004
We present an algorithm to compute arbitrary multi-loop massive Feynman diagrams in the region where the typical energy scale \sqrt{s} is much larger than the typical mass scale M, i.e.
A. Denner, Abe, Abe, Actis, Aglietti, Aglietti, Aguilar-Saavedra, Beccaria, Beenakker, Beenakker, Binoth, Binoth, Binoth, Ciafaloni, Ciafaloni, Ciafaloni, Ciafaloni, Ciafaloni, Ciafaloni, Ciafaloni, Degrassi, Denner, Denner, Denner, Denner, Denner, Denner, Eden, Fadin, Ferroglia, Feucht, Feucht, Hepp, Hori, Itzykson, Kinoshita, Kuroda, Kühn, Kühn, Kühn, Kühn, Melles, Melles, Melles, Melles, Melles, Melles, Nakanishi, Passarino, Passarino, Pozzorini, Roth, S. Pozzorini   +52 more
core   +1 more source

Kolmogorov spectrum consistent optimization for multi-scale flow decomposition [PDF]

Physics of Fluids, 2014
Multi-scale analysis is widely adopted in turbulence research for studying flow structures corresponding to specific length scales in the Kolmogorov spectrum. In the present work, a new methodology based on novel optimization techniques for scale decomposition is introduced, which leads to a bandpass filter with prescribed properties. With this filter,
Mishra, M., Liu, X., Skote, M., Fu, C.-W.   +3 more
openaire   +3 more sources

Predicting Epileptogenic Tubers in Patients With Tuberous Sclerosis Complex Using a Fusion Model Integrating Lesion Network Mapping and Machine Learning

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu, Qi Wang, Suhui Kuang, Dezhi Cao, Ping Ding, Shaohui Zhang, Haihua Wei, Zhirong Wei, Jinshan Xu, Xinyu Huang, Bing Liu, Shuli Liang   +11 more
wiley   +1 more source

Optimal Speech Signal Processing Based on Dynamic Multi-Scale Analysis

IEEE Access
To enhance the quality of speech signals, this paper introduces a novel speech signal processing method that integrates Dynamic Multi-Scale (DMS) and Adaptive Error Minimization (AEM) techniques.
Zefei Guo, Xiao Li, Yuchen Zhang
doaj   +1 more source