Journals
Advanced Photonics
Photonics Insights
Advanced Photonics Nexus
Photonics Research
Advanced Imaging
View All Journals
Chinese Optics Letters
High Power Laser Science and Engineering
Articles
Optics
Physics
Geography
View All Subjects
Conferences
CIOP
HPLSE
AP
View All Events
News
About CLP
Search by keywords or author
Login
Registration
Login in
Registration
Search
Search
Articles
Journals
News
Advanced Search
Top Searches
metasurface
laser
polarization
nir
lithium niobate
optical coherence tomography
Journals >
Acta Optica Sinica >
Volume 41 >
Issue 10 >
Page 1028001 > Article
Acta Optica Sinica
Vol. 41, Issue 10, 1028001 (2021)
Real-Time Object Detection in Remote Sensing Images Based on Embedded System
Yuanjun Nong and Junjie Wang
*
Author Affiliations
School of Engineering, Ocean University of China, Qingdao, Shandong 266100, China
show less
DOI:
10.3788/AOS202141.1028001
Cite this Article
Set citation alerts
Yuanjun Nong, Junjie Wang. Real-Time Object Detection in Remote Sensing Images Based on Embedded System[J]. Acta Optica Sinica, 2021, 41(10): 1028001
Copy Citation Text
EndNote(RIS)
BibTex
Plain Text
show less
Fig. 1.
Network structure of YOLOv3-tiny
Download full size
Fig. 2.
Detection flow of YOLOv3-tiny
Download full size
Fig. 3.
52×52 scale shallow features and 26×26 scale deep features
Download full size
Fig. 4.
Multi-scale prediction structure. (a) Multi-scale prediction before modified; (b) multi-scale prediction after modified
Download full size
Fig. 5.
Spatial attention module. (a) Original spatial attention module; (b) modified spatial attention module
Download full size
Fig. 6.
Network structure of YOLO-RS
Download full size
Fig. 7.
Loss curve during training process
Download full size
Fig. 8.
Test results of YOLO-RS
Download full size
Fig. 9.
Experiments on the embedded platform Jetson Xavier NX
Download full size
Fig. 10.
Comparison of detection accuracy and speed of different models
Download full size
Method
Input size
mAP /%
Recall /%
F1 /%
BFLOPS
Volume /MB
YOLOv3
608×608
80.07
81
81
139.64
246.5
YOLOv3-tiny
608×608
73.09
67
72
11.67
34.8
YOLO-RS
608×608
76.70
75
78
7.04
10.0
YOLOv3
512×512
79.61
76
80
99.02
246.5
YOLOv3-tiny
512×512
71.60
63
70
8.27
34.8
YOLO-RS
512×512
75.56
73
77
4.99
10.0
YOLOv3
416×416
77.04
70
77
65.37
246.5
YOLOv3-tiny
416×416
65.15
54
64
5.46
34.8
YOLO-RS
416×416
72.86
65
72
3.30
10.0
Table 1.
Detection performance of different methods on remote sensing test set
Method
Speed /(frame·s
-1
)
416×416
512×512
608×608
YOLOv3
8.1
6.3
4.6
YOLOv3-tiny
54.6
40.8
31.5
YOLO-RS
56.7
43.5
32.5
Table 2.
Detection speed of different methods on Jetson Xavier NX
Abstract
Get PDF(in Chinese)
Figures&Tables (12)
Equations (0)
References (19)
Cited By (7)
Get Citation
Copy Citation Text
Yuanjun Nong, Junjie Wang. Real-Time Object Detection in Remote Sensing Images Based on Embedded System[J]. Acta Optica Sinica, 2021, 41(10): 1028001
Download Citation
EndNote(RIS)
BibTex
Plain Text
Set citation alerts for the article
Tools
Share
Set citation alerts for the article
Save the article for my favorites
Paper Information
Category: Remote Sensing and Sensors
Received: Oct. 22, 2020
Accepted: Dec. 30, 2020
Published Online: May. 8, 2021
The Author Email: Wang Junjie (wjj@ouc.edu.cn)
DOI:
10.3788/AOS202141.1028001
Recommended Topics
laser devices and laser physics
Lasers and Laser Optics
Laser physics
laser manufacturing
Instrumentation, Measurement and Metrology
Set citation alerts for the article
Please enter your email address
Cancel
Confirm