Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Naziha Dhibi"'
Autor:
Chokri Ben Amar, Naziha Dhibi
Publikováno v:
Neural Processing Letters. 53:2221-2241
We propose, in this paper, a novel technique for large Laplacian boundary deformations using estimated rotations. The introduced method is used in the domain of Region of Interest (ROI) to align features of mesh based on Multi Mother Wavelet Neural N
Autor:
Naziha Dhibi, Chokri Ben Amar
Publikováno v:
International Journal of Machine Learning and Cybernetics. 11:2703-2717
In this paper, we propose a new 3D high mesh deformation technique to extract intuitive and interpretable deformation and alignment components. Our framework is based on a fast Beta wavelet transform for a multi-resolution analysis relying on multi-l
Autor:
Naziha Dhibi, Chokri Ben Amar
Publikováno v:
IET Image Processing. 13:2480-2486
The current study presents a new 3D mesh deformation process using multi-mother wavelet neural network architecture, which relies on genetic algorithm and multiresolution analysis. Classic forming algorithms begin with a predetermined network archite
Publikováno v:
Multimedia Tools and Applications. 76:20869-20887
We propose in this paper a 3D mesh compression algorithm for 3D deformation objects to facilitate the transmission of deformed object to another. This algorithm allows eliminating an object in the sequence of deformed objects and reducing the informa
Autor:
Chokri Ben Amar, Naziha Dhibi
Publikováno v:
Advances in Computational Intelligence ISBN: 9783030205171
IWANN (2)
IWANN (2)
This paper presents the implementation of genetic algorithm which aims at searching for an optimal or near optimal solution to the deformation 3D objects problem based on multi-mother wavelet neural network training. First, we introduce the problem o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e76c3cdd51dd10930e3f33c733f389ef
https://doi.org/10.1007/978-3-030-20518-8_9
https://doi.org/10.1007/978-3-030-20518-8_9
Publikováno v:
Artificial Neural Networks and Machine Learning – ICANN 2018 ISBN: 9783030014209
ICANN (2)
ICANN (2)
The 3D deformation and simulation process frequently include much iteration of geometric design changes. We propose in this paper a study on the influence of wavelet number change in the wavelet neural network architecture for 3D mesh deformation met
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d3b47d407176c45479585acc4f0085e0
https://doi.org/10.1007/978-3-030-01421-6_52
https://doi.org/10.1007/978-3-030-01421-6_52
Publikováno v:
ICMV
Triangular surface are now widely used for modeling three-dimensional object, since these models are very high resolution and the geometry of the mesh is often very dense, it is then necessary to remesh this object to reduce their complexity, the mes
Publikováno v:
3D Research. 7
This paper deals with the features of a novel technique for large Laplacian boundary deformations using estimated rotations. The proposed method is based on a Multi Library Wavelet Neural Network structure founded on several mother wavelet families (
Publikováno v:
Advanced Concepts for Intelligent Vision Systems ISBN: 9783319259024
ACIVS
ACIVS
This paper addressed the problem of Spherical Mesh parameterization. The main contribution of this work was to propose an effective optimization scheme to compute such parameterization, and to have an algorithm exposing a property of global convergen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a70d4fe9395a6da6c1ec14bc305804ff
https://doi.org/10.1007/978-3-319-25903-1_47
https://doi.org/10.1007/978-3-319-25903-1_47
Publikováno v:
2012 16th IEEE Mediterranean Electrotechnical Conference.
This paper is part of the study implementation of a new training algorithm for multi-dimensional wavelet networks called MDWNN-GA-MA using the genetic algorithm and multiresolution analysis to approximate and model 3D objects. This new approach aims