Noise distance driven fuzzy clustering based on adaptive weighted local information and entropy-like divergence kernel for robust image segmentation

[1]  Tao Tang,et al.  A Kernel Clustering Algorithm With Fuzzy Factor: Application to SAR Image Segmentation , 2014, IEEE Geoscience and Remote Sensing Letters.

[2]  L. Bregman.  The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming , 1967 .

[3]  Frank Nielsen,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. 1 Total Bregman Divergence and its Applications to DTI Analysis , 2022 .

[4]  Anil K. Jain,et al.  Integrating Faces and Fingerprints for Personal Identification , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  G. Evelin Suji,et al.  MRI Brain Image Segmentation using Advanced Fuzzy C-Means Algorithm , 2012 .

[6]  A. Plastino,et al.  Metric character of the quantum Jensen-Shannon divergence , 2008, 0801.1586.

[7]  Aly A. Farag,et al.  A modified fuzzy c-means algorithm for bias field estimation and segmentation of MRI data , 2002, IEEE Transactions on Medical Imaging.

[8]  M. Ayres,et al.  Jensen's inequality predicts effects of environmental variation. , 1999, Trends in ecology & evolution.

[9]  Xiaoqiang Yang,et al.  Robust credibilistic fuzzy local information clustering with spatial information constraints , 2020, Digit. Signal Process..

[10]  Wichian Chotiwattana,et al.  Noise Clustering Algorithm based on Kernel Method , 2009, 2009 IEEE International Advance Computing Conference.

[11]  R.N. Dave,et al.  Robust fuzzy clustering algorithms , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[12]  S. Sra.  Positive definite matrices and the S-divergence , 2011, 1110.1773.

[13]  Alex Smola,et al.  Kernel methods in machine learning , 2007, math/0701907.

[14]  Robert Jenssen,et al.  The Cauchy-Schwarz divergence and Parzen windowing: Connections to graph theory and Mercer kernels , 2006, J. Frankl. Inst..

[15]  Pedro W. Lamberti,et al.  Monoparametric family of metrics derived from classical Jensen–Shannon divergence , 2017, 1709.10153.

[16]  Daoqiang Zhang,et al.  Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation , 2007, Pattern Recognit..

[17]  Jing Bai,et al.  Application of Support Vector Machine with Modified Gaussian Kernel in A Noise-Robust Speech Recognition System , 2008, 2008 IEEE International Symposium on Knowledge Acquisition and Modeling Workshop.

[18]  Tin Kam Ho,et al.  KL-divergence kernel regression for non-Gaussian fingerprint based localization , 2011, 2011 International Conference on Indoor Positioning and Indoor Navigation.

[19]  Edwin R. Hancock,et al.  Graph Kernels from the Jensen-Shannon Divergence , 2012, Journal of Mathematical Imaging and Vision.

[20]  Rehna Kalam,et al.  GAUSSIAN KERNEL BASED FUZZY C-MEANS CLUSTERING ALGORITHM FOR IMAGE SEGMENTATION , 2016 .

[21]  Maoguo Gong,et al.  Change Detection in Synthetic Aperture Radar Images based on Image Fusion and Fuzzy Clustering , 2012, IEEE Transactions on Image Processing.

[22]  Stelios Krinidis,et al.  A Robust Fuzzy Local Information C-Means Clustering Algorithm , 2010, IEEE Transactions on Image Processing.

[23]  Eric P. Xing,et al.  Nonextensive Information Theoretic Kernels on Measures , 2009, J. Mach. Learn. Res..

[24]  Eric P. Xing,et al.  Nonextensive entropic kernels , 2008, ICML '08.

[25]  Dominik Endres,et al.  A new metric for probability distributions , 2003, IEEE Transactions on Information Theory.

[26]  Tony Jebara,et al.  Probability Product Kernels , 2004, J. Mach. Learn. Res..

[27]  Swagatam Das,et al.  Geometric divergence based fuzzy clustering with strong resilience to noise features , 2016, Pattern Recognit. Lett..

[28]  Noureddine Melikechi,et al.  A Family of Chisini Mean Based Jensen-Shannon Divergence Kernels , 2015, 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA).

[29]  Kenji Fukumizu,et al.  Semigroup Kernels on Measures , 2005, J. Mach. Learn. Res..

[30]  Nuno Vasconcelos,et al.  A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications , 2003, NIPS.

[31]  J. Bezdek,et al.  FCM: The fuzzy c-means clustering algorithm , 1984 .

[32]  Zhiyan Han,et al.  Speech emotion recognition based on Gaussian kernel nonlinear proximal support vector machine , 2017, 2017 Chinese Automation Congress (CAC).

[33]  Olga Perepelkina,et al.  Robust algorithm for remote photoplethysmography in realistic conditions , 2020, Digit. Signal Process..

[34]  Le Hoang Son,et al.  Picture fuzzy clustering: a new computational intelligence method , 2016, Soft Comput..

[35]  Shuying Li,et al.  Unsupervised Change Detection Using Fast Fuzzy Clustering for Landslide Mapping from Very High-Resolution Images , 2018, Remote. Sens..

[36]  Daoqiang Zhang,et al.  Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[37]  Miin-Shen Yang,et al.  Alternative c-means clustering algorithms , 2002, Pattern Recognit..

[38]  Daniel Boley,et al.  Bregman Divergences and Triangle Inequality , 2013, SDM.

[39]  Dong-Chul Park,et al.  MPEG Video Traffic Modeling and Classification Using Fuzzy C-Means Algorithm with Divergence-Based Kernel , 2006, ICONIP.

[40]  Miin-Shen Yang,et al.  A Gaussian kernel-based fuzzy c-means algorithm with a spatial bias correction , 2008, Pattern Recognit. Lett..

[41]  Dong-Chul Park,et al.  Classification of audio signals using Fuzzy c-Means with divergence-based Kernel , 2009, Pattern Recognit. Lett..

[42]  Nor Ashidi Mat Isa,et al.  Adaptive fuzzy-K-means clustering algorithm for image segmentation , 2010, IEEE Transactions on Consumer Electronics.

[43]  Yanhui Guo,et al.  A Novel Color Image Segmentation Approach Based on Neutrosophic Set and Modified Fuzzy c-Means , 2013, Circuits Syst. Signal Process..

[44]  Ondrej Krejcar,et al.  Fuzzy c-means clustering using Jeffreys-divergence based similarity measure , 2020, Appl. Soft Comput..

[45]  Nuno Vasconcelos,et al.  Probabilistic kernels for the classification of auto-regressive visual processes , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[46]  Swagatam Das,et al.  k-Means clustering with a new divergence-based distance metric: Convergence and performance analysis , 2017, Pattern Recognit. Lett..

[47]  Nizar Bouguila,et al.  Bayesian hybrid generative discriminative learning based on finite Liouville mixture models , 2011, Pattern Recognit..

[48]  Wenzhong Shi,et al.  A Novel Adaptive Fuzzy Local Information $C$ -Means Clustering Algorithm for Remotely Sensed Imagery Classification , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[49]  Hal Daumé,et al.  Generative Kernels for Exponential Families , 2011, AISTATS.