Performance evaluation of low resolution visual tracking for unmanned aerial vehicles

Yong Wang; Xian Wei; Hao Shen; Jilin Hu; Lingkun Luo

doi:10.1007/s00521-020-05067-3

Performance evaluation of low resolution visual tracking for unmanned aerial vehicles

Yong Wang, Xian Wei^*, Hao Shen, Jilin Hu, Lingkun Luo

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

1 Citation (Scopus)

Original language	English
Journal	Neural Computing and Applications
Volume	33
Issue number	7
Pages (from-to)	2229-2248
Number of pages	20
ISSN	0941-0643
DOIs	https://doi.org/10.1007/s00521-020-05067-3
Publication status	Published - Apr 2021

Bibliographical note

Funding Information:
This work was partially supported by National Science Found for Young Scholars under Grant No. 61806186, State Key Laboratory of Robotics and System (HIT) under Grant No. SKLRS-2019-KF-15, the program ‘Construction of Fujian Research Institute on Intelligent Logistics Industry Technology’ under Grant No. 2018H2001, CAS Pioneer Hundred Talents Program (Type C) under Grant No. 2017-122, and the program ‘Quanzhou Science and Technology Plan’ under Grant No. 2019C112, No. 2019C011R and No. 2019STS08.

Publisher Copyright:
© 2020, Springer-Verlag London Ltd., part of Springer Nature.

Keywords

Fusion algorithm
Image enhancement
Low resolution dataset
UAV tracking

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10.1007/s00521-020-05067-3

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@article{628dc81204f5467ab857e409fa991610,

title = "Performance evaluation of low resolution visual tracking for unmanned aerial vehicles",

keywords = "Fusion algorithm, Image enhancement, Low resolution dataset, UAV tracking",

author = "Yong Wang and Xian Wei and Hao Shen and Jilin Hu and Lingkun Luo",

note = "Funding Information: This work was partially supported by National Science Found for Young Scholars under Grant No. 61806186, State Key Laboratory of Robotics and System (HIT) under Grant No. SKLRS-2019-KF-15, the program {\textquoteleft}Construction of Fujian Research Institute on Intelligent Logistics Industry Technology{\textquoteright} under Grant No. 2018H2001, CAS Pioneer Hundred Talents Program (Type C) under Grant No. 2017-122, and the program {\textquoteleft}Quanzhou Science and Technology Plan{\textquoteright} under Grant No. 2019C112, No. 2019C011R and No. 2019STS08. Publisher Copyright: {\textcopyright} 2020, Springer-Verlag London Ltd., part of Springer Nature.",

year = "2021",

month = apr,

doi = "10.1007/s00521-020-05067-3",

language = "English",

volume = "33",

pages = "2229--2248",

journal = "Neural Computing and Applications",

issn = "0941-0643",

publisher = "Springer",

number = "7",

}

TY - JOUR

T1 - Performance evaluation of low resolution visual tracking for unmanned aerial vehicles

AU - Wang, Yong

AU - Wei, Xian

AU - Shen, Hao

AU - Hu, Jilin

AU - Luo, Lingkun

N1 - Funding Information: This work was partially supported by National Science Found for Young Scholars under Grant No. 61806186, State Key Laboratory of Robotics and System (HIT) under Grant No. SKLRS-2019-KF-15, the program ‘Construction of Fujian Research Institute on Intelligent Logistics Industry Technology’ under Grant No. 2018H2001, CAS Pioneer Hundred Talents Program (Type C) under Grant No. 2017-122, and the program ‘Quanzhou Science and Technology Plan’ under Grant No. 2019C112, No. 2019C011R and No. 2019STS08. Publisher Copyright: © 2020, Springer-Verlag London Ltd., part of Springer Nature.

PY - 2021/4

Y1 - 2021/4

KW - Fusion algorithm

KW - Image enhancement

KW - Low resolution dataset

KW - UAV tracking

UR - http://www.scopus.com/inward/record.url?scp=85087016717&partnerID=8YFLogxK

U2 - 10.1007/s00521-020-05067-3

DO - 10.1007/s00521-020-05067-3

M3 - Journal article

AN - SCOPUS:85087016717

VL - 33

SP - 2229

EP - 2248

JO - Neural Computing and Applications

JF - Neural Computing and Applications

SN - 0941-0643

IS - 7

ER -

Performance evaluation of low resolution visual tracking for unmanned aerial vehicles

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Keywords

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