loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Francisco Rodolfo Barbosa-Anda 1 ; Cyril Briand 1 ; Frédéric Lerasle 1 and Alhayat Ali Mekonnen 2

Affiliations: 1 CNRS, LAAS, Univ de Toulouse, UPS and LAAS, France ; 2 CNRS and LAAS, France

ISBN: 978-989-758-171-7

Keyword(s): Mathematical Programming, Soft-Cascade, Machine Learning, Object Detection.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Linear Programming ; Methodologies and Technologies ; Operational Research ; Optimization ; Symbolic Systems

Abstract: In this paper, the problem of minimizing the mean response-time of a soft-cascade detector is addressed. A soft-cascade detector is a machine learning tool used in applications that need to recognize the presence of certain types of object instances in images. Classical soft-cascade learning methods select the weak classifiers that compose the cascade, as well as the classification thresholds applied at each cascade level, so that a desired detection performance is reached. They usually do not take into account its mean response-time, which is also of importance in time-constrained applications. To overcome that, we consider the threshold selection problem aiming to minimize the computation time needed to detect a target object in an image (i.e., by classifying a set of samples). We prove the NP-hardness of the problem and propose a mathematical model that takes benefit from several dominance properties, which are put into evidence. On the basis of computational experiments, we show t hat we can provide a faster cascade detector, while maintaining the same detection performances. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.81.220.239

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Barbosa-Anda, F.; Barbosa-Anda, F.; Briand, C.; Lerasle, F. and Mekonnen, A. (2016). Mean Response-Time Minimization of a Soft-Cascade Detector.In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 252-260. DOI: 10.5220/0005700702520260

@conference{icores16,
author={Francisco Rodolfo Barbosa{-}Anda. and Francisco Rodolfo Barbosa{-}Anda. and Cyril Briand. and Frédéric Lerasle. and Alhayat Ali Mekonnen.},
title={Mean Response-Time Minimization of a Soft-Cascade Detector},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2016},
pages={252-260},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005700702520260},
isbn={978-989-758-171-7},
}

TY - CONF

JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Mean Response-Time Minimization of a Soft-Cascade Detector
SN - 978-989-758-171-7
AU - Barbosa-Anda, F.
AU - Barbosa-Anda, F.
AU - Briand, C.
AU - Lerasle, F.
AU - Mekonnen, A.
PY - 2016
SP - 252
EP - 260
DO - 10.5220/0005700702520260

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.