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A Sequential Niche Technique for Multimodal Function Optimization
TLDR
An algorithm based on a traditional genetic algorithm that involves iterating the GA but uses knowledge gained during one iteration to avoid re-searching, on subsequent iterations, regions of problem space where solutions have already been found. Expand
Incremental Eigenanalysis for Classification
TLDR
A new constructive method is described for incrementally adding observations to an eigenspace model to explicitly account for a change in origin as well as achange in the number of eigenvectors needed in the basis set. Expand
Fast and Effective Feature-Preserving Mesh Denoising
TLDR
A simple and fast mesh denoising method that can remove noise effectively while preserving mesh features such as sharp edges and corners is presented, and the convergence of the vertex position updating approach is proved. Expand
An overview of Genetic Algorithms: Pt1, Fundamentals
TLDR
Genetic Algorithms (GAs) are adaptive methods which may be used to solve search and optimisation problems based on the genetic processes of biological organisms, which simulate those processes in natural populations which are essential to evolution. Expand
Reverse engineering of geometric models - an introduction
TLDR
Specific issues addressed include characterization of geometric models and related surface representations, segmentation and surface fitting for simple and free-form shapes, multiple view combination and creating consistent and accurate B-rep models. Expand
Merging and Splitting Eigenspace Models
We present new deterministic methods that, given two eigenspace models-each representing a set of n-dimensional observations-will: 1) merge the models to yield a representation of the union of theExpand
A Shape‐Preserving Approach to Image Resizing
TLDR
A novel image resizing method which attempts to ensure that important local regions undergo a geometric similarity transformation, and at the same time, to preserve image edge structure, and is efficient, and offers a closed form solution. Expand
Fast mesh segmentation using random walks
TLDR
A random walk method used previously for image segmentation is extended to give algorithms for both interactive and automatic mesh segmentation, which is extremely efficient, and scales almost linearly with increasing number of faces. Expand
Mesh saliency via spectral processing
TLDR
The benefits of the proposed method are further evaluated in applications such as mesh simplification, mesh segmentation, and scan integration, where it is shown how incorporating mesh saliency can provide improved results. Expand
Non-rigid 3D Shape Retrieval
TLDR
Evaluation results and comparison analyses described in this paper not only show the bright future in researches of non-rigid 3D shape retrieval but also point out several promising research directions in this topic. Expand
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