A Vehicle Detection Algorithm Based on Deep Belief Network

المؤلفون المشاركون

Wang, Hai
Cai, Yingfeng
Chen, Long

المصدر

The Scientific World Journal

العدد

المجلد 2014، العدد 2014 (31 ديسمبر/كانون الأول 2014)، ص ص. 1-7، 7ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2014-05-14

دولة النشر

مصر

عدد الصفحات

7

التخصصات الرئيسية

الطب البشري
تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

Vision based vehicle detection is a critical technology that plays an important role in not only vehicle active safety but also road video surveillance application.

Traditional shallow model based vehicle detection algorithm still cannot meet the requirement of accurate vehicle detection in these applications.

In this work, a novel deep learning based vehicle detection algorithm with 2D deep belief network (2D-DBN) is proposed.

In the algorithm, the proposed 2D-DBN architecture uses second-order planes instead of first-order vector as input and uses bilinear projection for retaining discriminative information so as to determine the size of the deep architecture which enhances the success rate of vehicle detection.

On-road experimental results demonstrate that the algorithm performs better than state-of-the-art vehicle detection algorithm in testing data sets.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Wang, Hai& Cai, Yingfeng& Chen, Long. 2014. A Vehicle Detection Algorithm Based on Deep Belief Network. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1050489

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Wang, Hai…[et al.]. A Vehicle Detection Algorithm Based on Deep Belief Network. The Scientific World Journal No. 2014 (2014), pp.1-7.
https://search.emarefa.net/detail/BIM-1050489

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Wang, Hai& Cai, Yingfeng& Chen, Long. A Vehicle Detection Algorithm Based on Deep Belief Network. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-7.
https://search.emarefa.net/detail/BIM-1050489

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1050489