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Cited by 93Advanced Neural Network ApplicationsVideo Surveillance and Tracking MethodsAdvanced SAR Imaging Techniques

The DOI matches its Crossref record.

A UAV Detection Algorithm Based on an Artificial Neural Network

Open access
Zhang, Hao, Cao, Conghui, Xu, Lingwei, Gulliver, T. Aaron·2018·IEEE Access
DOI 10.1109/access.2018.2831911
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Abstract

This work was supported in part by the National Natural Science Foundation of China under Grant 61701462 and Grant 41527901, in part by the Qingdao National Laboratory for Marine Science and Technology under Grant 2017ASKJ01, in part by the Qingdao Science and Technology Plan under Grant 17-1-1-7-jch, in part by the Fundamental Research Funds for the Central Universities under Grant 201713018, in part by the Shandong Province Natural Science Foundation under Grant ZR2017BF023, in part by the China Postdoctoral Science Foundation funded project under Grant 2017M612223, and in part by the Shandong Province Postdoctoral Innovation Project under Grant 201703032.

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Crossref · 10.1109/access.2018.2831911

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Research works printed but not linked: 30

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Cited by

Metadata

Authors
Zhang, H., Cao, C., Xu, L., & Gulliver, T. A.
Affiliations
  • Ocean University of China (CN)
  • Qingdao University of Science and Technology (CN)
  • University of Victoria (CA)
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2018
Volume
6
Pages
24720-24728
ISSN
2169-3536 (ISSN-L)
DOI
10.1109/access.2018.2831911
OpenAlex
W2801173680
Cited by
93
References
0
Citations by year
2026: 6 · 2025: 6 · 2024: 16 · 2023: 6 · 2022: 14 · 2021: 19 · 2020: 13 · 2019: 10 · 2018: 3
FWCI
5.63
Type
journal article
Language
en
Open access
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/OAPA.html (vor)
Locations
  • IEEE Access (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Natural Science Foundation of China (61701462, 41527901)
  • Qingdao National Laboratory for Marine Science and Technology (2017ASKJ01)
  • Qingdao Science and Technology Plan (17-1-1-7-jch)
  • Fundamental Research Funds for the Central Universities (201713018)
  • Shandong Province Natural Science Foundation (ZR2017BF023)
  • China Postdoctoral Science Foundation (2017M612223)
  • Shandong Province Postdoctoral Innovation Project (201703032)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
  • Physical Sciences › Engineering › Aerospace Engineering › Advanced SAR Imaging Techniques
Keywords
unmanned aerial vehicle detection, artificial neural networks, object detection

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.