Data clustering using a model granular magnet
Neural Computation
2D spiral pattern recognition with possibilistic measures
Pattern Recognition Letters
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computer and Robot Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift, Mode Seeking, and Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Kernel density estimation with adaptive varying window size
Pattern Recognition Letters
Data Clustering Using Evidence Accumulation
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
Terrain Analysis Using Radar Shape-from-Shading
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Robust Adaptive-Scale Parametric Model Estimation for Computer Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Variational learning for Gaussian mixture models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The estimation of the gradient of a density function, with applications in pattern recognition
IEEE Transactions on Information Theory
IEEE Transactions on Neural Networks
Gradient-based manipulation of nonparametric entropy estimates
IEEE Transactions on Neural Networks
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Kernel bandwidth estimation for nonparametric modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Envisioning dynamic quantum clustering in information retrieval
QI'11 Proceedings of the 5th international conference on Quantum interaction
High-performance dynamic quantum clustering on graphics processors
Journal of Computational Physics
Multi-elitist immune clonal quantum clustering algorithm
Neurocomputing
3D modeling of multiple-object scenes from sets of images
Pattern Recognition
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This paper introduces a new nonparametric estimation approach inspired from quantum mechanics. Kernel density estimation associates a function to each data sample. In classical kernel estimation theory the probability density function is calculated by summing up all the kernels. The proposed approach assumes that each data sample is associated with a quantum physics particle that has a radial activation field around it. Schrodinger differential equation is used in quantum mechanics to define locations of particles given their observed energy level. In our approach, we consider the known location of each data sample and we model their corresponding probability density function using the analogy with the quantum potential function. The kernel scale is estimated from distributions of K-nearest neighbours statistics. In order to apply the proposed algorithm to pattern classification we use the local Hessian for detecting the modes in the quantum potential hypersurface. Each mode is assimilated with a nonparametric class which is defined by means of a region growing algorithm. We apply the proposed algorithm on artificial data and for the topography segmentation from radar images of terrain.