After a brief survey on well established methods for image classification, we focus on a recently proposed Multiple Istance Learning (MIL) method which is suitable for applications in image processing. In particular the method is based on a mixed integer nonlinear formulation of the optimization problem to be solved for MIL purposes. The algorithm is applied to a set of color images (Red, Green, Blue, RGB) with the objective of classifying the images containing some specific pattern. The results of our experimentation are reported.

A multiple instance learning algorithm for color images classification

Astorino Annabella;Vocaturo Eugenio
2018

Abstract

After a brief survey on well established methods for image classification, we focus on a recently proposed Multiple Istance Learning (MIL) method which is suitable for applications in image processing. In particular the method is based on a mixed integer nonlinear formulation of the optimization problem to be solved for MIL purposes. The algorithm is applied to a set of color images (Red, Green, Blue, RGB) with the objective of classifying the images containing some specific pattern. The results of our experimentation are reported.
2018
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Istituto di Nanotecnologia - NANOTEC - Sede Secondaria Rende (CS)
9781450365277
Image classification
Lagrangian Relaxation
Multiple Instance Learning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/358806
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