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Authors: Ignazio Gallo and Angelo Nodari

Affiliation: University of Insubria, Italy

Keyword(s): Object detection, Neural networks, Multiple neural networks.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Image and Video Analysis ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Segmentation and Grouping ; Sensor Networks ; Soft Computing

Abstract: Multiple neural network systems have become popular techniques for tackling complex tasks, often giving improved performance compared to a single network. In this study we propose an innovative detection algorithm in image analysis using a multiple neural network approach where many neural networks are jointly used to solve the object detection problem. We use a group of networks configured with different parameters and features, then combines them in order to obtain new networks. The topology of the set of neural networks is statically configured as a tree where the root node produces in output the detection map. This work represents a preliminary study through which we want to move from detection to segmentation and recognition of objects of interest. We have compared our model with other detection algorithms using a standard dataset and the results are encouraging. The results highlight the advantages and problems that will guide the evolution of the proposed model.

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Paper citation in several formats:
Gallo, I. and Nodari, A. (2011). LEARNING OBJECT DETECTION USING MULTIPLE NEURAL NETWORKS. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP; ISBN 978-989-8425-47-8; ISSN 2184-4321, SciTePress, pages 131-136. DOI: 10.5220/0003328301310136

@conference{visapp11,
author={Ignazio Gallo. and Angelo Nodari.},
title={LEARNING OBJECT DETECTION USING MULTIPLE NEURAL NETWORKS},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP},
year={2011},
pages={131-136},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003328301310136},
isbn={978-989-8425-47-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the International Conference on Computer Vision Theory and Applications (VISIGRAPP 2011) - VISAPP
TI - LEARNING OBJECT DETECTION USING MULTIPLE NEURAL NETWORKS
SN - 978-989-8425-47-8
IS - 2184-4321
AU - Gallo, I.
AU - Nodari, A.
PY - 2011
SP - 131
EP - 136
DO - 10.5220/0003328301310136
PB - SciTePress

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