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Medulloblastoma (MB) is a type of brain cancer that represent roughly 25% of all brain tumors in children. In the anaplastic medulloblastoma subtype, it is important to identify the degree of irregularity and lack of organizations of cells as this correla ...
The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...
The extraction of student behavior is an important task in educational data mining. A common approach to detect similar behavior patterns is to cluster sequential data. Standard approaches identify clusters at each time step separately and typically show l ...
Diffusion LMS was originally conceived for online distributed parameter estimation in single-task environments where agents pursue a common objective. However, estimating distinct but correlated objects (multitask problems) is useful in many applications. ...
Distributed processing over networks relies on in-network processing and cooperation among neighboring agents. Cooperation is beneficial when agents share a common objective. However, in many applications, agents may belong to different clusters that pursu ...
In this work, a diffusion-type algorithm is proposed to solve multitask estimation problems where each cluster of nodes is interested in estimating its own optimum parameter vector in a distributed manner. The approach relies on minimizing a global mean-sq ...
We present a method for the unsupervised segmentation of textured images using Potts functionals, which are a piecewise-constant variant of the Mumford and Shah functionals. We propose a minimization strategy based on the alternating direction method of mu ...
Medulloblastoma (MB) is a type of brain cancer that represent roughly 25% of all brain tumors in children. In the anaplastic medulloblastoma subtype, it is important to identify the degree of irregularity and lack of organizations of cells as this correlat ...
In this paper, we tackle the problem of unsupervised classification of hyperspectral images. We propose a clustering method based on graphs representing the data structure, which is assumed to be an union of multiple manifolds. The method constraints the p ...
Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy lo ...