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Piecewise Convex Multiple-Model Endmember Detection and Spectral Unmixing
A hyperspectral endmember detection and spectral unmixing algorithm that finds multiple sets of endmembers is presented. Hyperspectral data are often nonconvex. The Piecewise Convex Multiple-ModelExpand
  • 48
  • 5
  • Open Access
Insult Detection in Social Network Comments Using Possibilistic Based Fusion Approach
This paper aims to propose a novel approach to automatically detect verbal offense in social network comments. It relies on a local approach that adapts the fusion method to different regions of theExpand
  • 9
  • 2
Fuzzy clustering with Learnable Cluster dependent Kernels
We propose a new relational clustering approach, called Fuzzy clustering with Learnable Cluster dependent Kernels (FLeCK), that learns multiple kernels while seeking compact clusters. A GaussianExpand
  • 7
  • 2
Endoscopy video summarization based on unsupervised learning and feature discrimination
We propose a novel endoscopy video summarization approach based on unsupervised learning and feature discrimination. The proposed learning approach partitions the collection of video frames intoExpand
  • 17
Spatially-smooth piece-wise convex endmember detection
An endmember detection and spectral unmixing algorithm that uses both spatial and spectral information is presented. This method, Spatial Piece-wise Convex Multiple Model Endmember Detection (SpatialExpand
  • 17
An Overview of Unsupervised and Semi-Supervised Fuzzy Kernel Clustering
For real-world clustering tasks, the input data is typically not easily separable due to the highly complex data structure or when clusters vary in size, density and shape. Kernel-based clusteringExpand
  • 6
  • Open Access
Endoscopy video summarisation using novel relational motion histogram descriptor and semi-supervised clustering
In this paper, we propose a novel system for capsule endoscopy (CE) summarisation that has two main components. The first component consists of the Semi-Supervised Clustering and Local Scale LearningExpand
  • 2
Fuzzy relational kernel clustering with Local Scaling Parameter Learning
  • Ouiem Bchir, H. Frigui
  • Computer Science
  • IEEE International Workshop on Machine Learning…
  • 7 October 2010
We introduce a new fuzzy relational clustering technique with Local Scaling Parameter Learning (LSPL). The proposed approach learns the underlying cluster dependent dissimilarity measure whileExpand
  • 5
Generic Evaluation Metrics for Hyperspectral Data Unmixing
AbstractWe propose novel generic performance metric for hyperspectral unmixing techniques. This relative metric compares two abundance matrices. The first one represents the unmixing result. TheExpand
  • 5
Multiple model endmember detection based on spectral and spatial information
We introduce a new spectral mixture analysis approach. Unlike most available approaches that only use the spectral information, this approach uses the spectral and spatial information available inExpand
  • 5