A Multibranch Object Detection Method for Traffic Scenes
Joint Authors
Feng, Jiangfan
Wang, Fanjie
Feng, Siqin
Peng, Yongrong
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-11
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
The performance of convolutional neural network- (CNN-) based object detection has achieved incredible success.
Howbeit, existing CNN-based algorithms suffer from a problem that small-scale objects are difficult to detect because it may have lost its response when the feature map has reached a certain depth, and it is common that the scale of objects (such as cars, buses, and pedestrians) contained in traffic images and videos varies greatly.
In this paper, we present a 32-layer multibranch convolutional neural network named MBNet for fast detecting objects in traffic scenes.
Our model utilizes three detection branches, in which feature maps with a size of 16 × 16, 32 × 32, and 64 × 64 are used, respectively, to optimize the detection for large-, medium-, and small-scale objects.
By means of a multitask loss function, our model can be trained end-to-end.
The experimental results show that our model achieves state-of-the-art performance in terms of precision and recall rate, and the detection speed (up to 33 fps) is fast, which can meet the real-time requirements of industry.
American Psychological Association (APA)
Feng, Jiangfan& Wang, Fanjie& Feng, Siqin& Peng, Yongrong. 2019. A Multibranch Object Detection Method for Traffic Scenes. Computational Intelligence and Neuroscience،Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1129424
Modern Language Association (MLA)
Feng, Jiangfan…[et al.]. A Multibranch Object Detection Method for Traffic Scenes. Computational Intelligence and Neuroscience No. 2019 (2019), pp.1-16.
https://search.emarefa.net/detail/BIM-1129424
American Medical Association (AMA)
Feng, Jiangfan& Wang, Fanjie& Feng, Siqin& Peng, Yongrong. A Multibranch Object Detection Method for Traffic Scenes. Computational Intelligence and Neuroscience. 2019. Vol. 2019, no. 2019, pp.1-16.
https://search.emarefa.net/detail/BIM-1129424
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1129424