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Journal ArticleDOI

Accelerated nonrigid image registration using improved Levenberg–Marquardt method

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TLDR
A dedicated optimization method is proposed for nonrigid CT image registration based on Levenberg–Marquardt (L-M) optimization and a linear search for the trial step is introduced to enhance performance.
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This article is published in Information Sciences.The article was published on 2018-01-01. It has received 19 citations till now. The article focuses on the topics: Image registration & Levenberg–Marquardt algorithm.

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Citations
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Journal ArticleDOI

Stability Analysis of the Modified Levenberg–Marquardt Algorithm for the Artificial Neural Network Training

TL;DR: A modified Levenberg–Marquardt algorithm is proposed for the artificial neural network learning containing the training and testing stages and error stability and weights boundedness are assured based on the Lyapunov technique.
Journal ArticleDOI

A comparison between the application of empirical and ANN methods for estimation of daily global solar radiation in Iran

TL;DR: In this paper, the authors compared the performance and suitability of different types of models for estimation of daily global solar radiation in Iran, based on duration of sunshine hours and diurnal air temperature.
Journal ArticleDOI

Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks

TL;DR: The paper shows that the local modification of the Levenberg-Marquardt algorithm significantly improves the algorithm’s performance for bigger networks.
Journal ArticleDOI

Multimodal brain tumor image segmentation using WRN-PPNet.

TL;DR: An automatic method, named wide residual network & pyramid pool network (WRN-PPNet), which can automatically segment glioma end to end is put forward and the experimental results show that the proposed method has a superior performance compared with the other state-of-the-art methods.
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Non-kinematic calibration of industrial robots using a rigid–flexible coupling error model and a full pose measurement method

TL;DR: Simulation results illustrate that the 36 error parameters of the proposed error model can be identified with improved accuracy and stability using the proposed approach, and are introduced to demonstrate the practical effectiveness of the approach in robot accuracy improvement.
References
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Journal ArticleDOI

Distinctive Image Features from Scale-Invariant Keypoints

TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
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A method for registration of 3-D shapes

TL;DR: In this paper, the authors describe a general-purpose representation-independent method for the accurate and computationally efficient registration of 3D shapes including free-form curves and surfaces, based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point.
Book ChapterDOI

SURF: speeded up robust features

TL;DR: A novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features), which approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster.
Journal ArticleDOI

Image registration methods: a survey

TL;DR: A review of recent as well as classic image registration methods to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas.
Journal ArticleDOI

Nonrigid registration using free-form deformations: application to breast MR images

TL;DR: The results clearly indicate that the proposed nonrigid registration algorithm is much better able to recover the motion and deformation of the breast than rigid or affine registration algorithms.