New efficient speed-up scheme for cascade implementation of SVM classifier

Jeonghyun Baek; Jisu Kim; Junhyuk Hyun; Euntai Kim

doi:10.1109/IJCNN.2015.7280810

New efficient speed-up scheme for cascade implementation of SVM classifier

Jeonghyun Baek, Jisu Kim, Junhyuk Hyun, Euntai Kim

Department of Electrical and Electronic Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset and show better rejection performance of negative samples than conventional method.

Original language	English
Title of host publication	2015 International Joint Conference on Neural Networks, IJCNN 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs	https://doi.org/10.1109/IJCNN.2015.7280810
Publication status	Published - 2015 Sep 28
Event	International Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland Duration: 2015 Jul 12 → 2015 Jul 17

Publication series

Name	Proceedings of the International Joint Conference on Neural Networks
Volume	2015-September

Other

Other	International Joint Conference on Neural Networks, IJCNN 2015
Country	Ireland
City	Killarney
Period	15/7/12 → 15/7/17

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

All Science Journal Classification (ASJC) codes

Software
Artificial Intelligence

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10.1109/IJCNN.2015.7280810

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Baek, J., Kim, J., Hyun, J., & Kim, E. (2015). New efficient speed-up scheme for cascade implementation of SVM classifier. In 2015 International Joint Conference on Neural Networks, IJCNN 2015 [7280810] (Proceedings of the International Joint Conference on Neural Networks; Vol. 2015-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IJCNN.2015.7280810

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title = "New efficient speed-up scheme for cascade implementation of SVM classifier",

abstract = "For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset and show better rejection performance of negative samples than conventional method.",

author = "Jeonghyun Baek and Jisu Kim and Junhyuk Hyun and Euntai Kim",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; International Joint Conference on Neural Networks, IJCNN 2015 ; Conference date: 12-07-2015 Through 17-07-2015",

year = "2015",

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day = "28",

doi = "10.1109/IJCNN.2015.7280810",

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Baek, J, Kim, J, Hyun, J & Kim, E 2015, New efficient speed-up scheme for cascade implementation of SVM classifier. in 2015 International Joint Conference on Neural Networks, IJCNN 2015., 7280810, Proceedings of the International Joint Conference on Neural Networks, vol. 2015-September, Institute of Electrical and Electronics Engineers Inc., International Joint Conference on Neural Networks, IJCNN 2015, Killarney, Ireland, 15/7/12. https://doi.org/10.1109/IJCNN.2015.7280810

New efficient speed-up scheme for cascade implementation of SVM classifier. / Baek, Jeonghyun; Kim, Jisu; Hyun, Junhyuk; Kim, Euntai.

2015 International Joint Conference on Neural Networks, IJCNN 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7280810 (Proceedings of the International Joint Conference on Neural Networks; Vol. 2015-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Kim, Jisu

AU - Hyun, Junhyuk

AU - Kim, Euntai

PY - 2015/9/28

Y1 - 2015/9/28

N2 - For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset and show better rejection performance of negative samples than conventional method.

AB - For intelligent vehicle applications, detecting pedestrian technique must be robust and perform in real time. In pedestrian detection, support vector machine (SVM) is one of the popular classifiers because of its robust performance. In this paper, we propose the new method to implement cascade SVM that enables fast rejection of negative samples. The proposed method is tested with INRIA person dataset and show better rejection performance of negative samples than conventional method.

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BT - 2015 International Joint Conference on Neural Networks, IJCNN 2015

PB - Institute of Electrical and Electronics Engineers Inc.

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New efficient speed-up scheme for cascade implementation of SVM classifier

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