Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism

Joint Authors

Li, Jinling
Hou, Qingshan
Xing, Jinsheng

Source

Complexity

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-08-28

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Philosophy

Abstract EN

Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks.

Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal.

Aiming at the shortcomings of the SSD algorithm, an improved algorithm based on the adaptive default box mechanism (ADB) is proposed.

The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters.

Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.

American Psychological Association (APA)

Li, Jinling& Hou, Qingshan& Xing, Jinsheng. 2020. Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142554

Modern Language Association (MLA)

Li, Jinling…[et al.]. Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1142554

American Medical Association (AMA)

Li, Jinling& Hou, Qingshan& Xing, Jinsheng. Multiobject Detection Algorithm Based on Adaptive Default Box Mechanism. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1142554

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1142554