Small Object Detection with Multiscale Features
Joint Authors
Yang, Zhong
Hu, Guo X.
Hu, Lei
Huang, Li
Han, Jia M.
Source
International Journal of Digital Multimedia Broadcasting
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-09-30
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Telecommunications Engineering
Electronic engineering
Information Technology and Computer Science
Abstract EN
The existing object detection algorithm based on the deep convolution neural network needs to carry out multilevel convolution and pooling operations to the entire image in order to extract a deep semantic features of the image.
The detection models can get better results for big object.
However, those models fail to detect small objects that have low resolution and are greatly influenced by noise because the features after repeated convolution operations of existing models do not fully represent the essential characteristics of the small objects.
In this paper, we can achieve good detection accuracy by extracting the features at different convolution levels of the object and using the multiscale features to detect small objects.
For our detection model, we extract the features of the image from their third, fourth, and 5th convolutions, respectively, and then these three scales features are concatenated into a one-dimensional vector.
The vector is used to classify objects by classifiers and locate position information of objects by regression of bounding box.
Through testing, the detection accuracy of our model for small objects is 11% higher than the state-of-the-art models.
In addition, we also used the model to detect aircraft in remote sensing images and achieved good results.
American Psychological Association (APA)
Hu, Guo X.& Yang, Zhong& Hu, Lei& Huang, Li& Han, Jia M.. 2018. Small Object Detection with Multiscale Features. International Journal of Digital Multimedia Broadcasting،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1170869
Modern Language Association (MLA)
Hu, Guo X.…[et al.]. Small Object Detection with Multiscale Features. International Journal of Digital Multimedia Broadcasting No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1170869
American Medical Association (AMA)
Hu, Guo X.& Yang, Zhong& Hu, Lei& Huang, Li& Han, Jia M.. Small Object Detection with Multiscale Features. International Journal of Digital Multimedia Broadcasting. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1170869
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1170869