Giorgio
University of Glasgow
My primary research interests are in the area of pattern recognition and machine learning. Within these areas, my work focuses on developing novel strategies to formalize, explain and visualize the pattern in data. My work encompasses different case studies. I worked on many aspects of feature selection in machine learning introducing the concept of graph-based feature selection. Such a framework is prone to parallelization making this family of algorithms highly scalable (i.e., suitable for Big Data analysis). Another important aspect I dealt with is the real-time factor of such techniques. This framework turns out to be also suitable for visual object tracking, demonstrating to improve tracking performance while maintaining high frame rates. Finally, I have also worked on soft-biometrics by taking into account user-centric aspects, such as personality.
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Inviato
Feature Selection Library
Feature Selection Library (MATLAB Toolbox)
quasi 4 anni fa | 63 download |
Inviato
Feature Selection Library
Feature Selection Library (MATLAB Toolbox)
oltre 5 anni fa | 4 download |
Inviato
Online Feature Selection for Visual Tracking
Visual Object Tracking - Tracker presented at BMVC 2016
quasi 6 anni fa | 3 download |
Inviato
Feature Selection by Eigenvector Centrality
Feature Selection by Eigenvector Centrality for Matlab - Updates 2016
oltre 7 anni fa | 1 download |
Inviato
Infinite Feature Selection
InfFS allows you to rank a huge list of feature, even more than 40000 features and 10000 samples.
oltre 7 anni fa | 1 download |
Risolto
Pizza!
Given a circular pizza with radius _z_ and thickness _a_, return the pizza's volume. [ _z_ is first input argument.] Non-scor...
oltre 7 anni fa
how to do feature selection and classification on abalone dataset using methods oter than LDA,QDA,PCA AND SEQUENTIAL FEATURE SELECTION.plz provide the suitable code for it.
Hi, most of the technique you cited are not doing feature selection PCA, for example, ia a dimensionality reduction method, you...
oltre 7 anni fa | 1