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Proceedings Paper

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms
Author(s): Valentina Negro Maggio; Luca Iocchi
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Paper Abstract

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Paper Details

Date Published: 14 February 2015
PDF: 5 pages
Proc. SPIE 9445, Seventh International Conference on Machine Vision (ICMV 2014), 94450X (14 February 2015); doi: 10.1117/12.2180688
Show Author Affiliations
Valentina Negro Maggio, Sapienza Univ. of Rome (Italy)
Luca Iocchi, Sapienza Univ. of Rome (Italy)
Sapienza Univ. of Rome (Italy)

Published in SPIE Proceedings Vol. 9445:
Seventh International Conference on Machine Vision (ICMV 2014)
Antanas Verikas; Branislav Vuksanovic; Petia Radeva; Jianhong Zhou, Editor(s)

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