Using deep learning in an embedded system for real-time target detection based on images from an unmanned aerial vehicle: vehicle detection as a case study-Reference-Cited by-同舟云学术

Using deep learning in an embedded system for real-time target detection based on images from an unmanned aerial vehicle: vehicle detection as a case study

Published:2023-03-14 Issue:1 Volume:16 Page:910-936
ISSN:1753-8947
Container-title:International Journal of Digital Earth
language:en
Short-container-title:International Journal of Digital Earth

Author:

Huang Fang¹^ORCID,Chen Shengyi¹^ORCID,Wang Qi²^ORCID,Chen Yingjie¹,Zhang Dandan³^ORCID

Affiliation:

1. School of Recourses and Environment, University of Electronic Science and Technology of China (UESTC), Chengdu, People’s Republic of China

2. Aerospace Information Research Institute (AIR), Chinese Academy of Sciences (CAS), Beijing, People’s Republic of China

3. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, People’s Republic of China

Funder

National Natural Science Foundation of China

Technological Innovation R&D Project of Chengdu Science and Technology Bureau

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences,Computer Science Applications,Software

Link

https://www.tandfonline.com/doi/pdf/10.1080/17538947.2023.2187465

Reference53 articles.

1. Counting Vehicles with Deep Learning in Onboard UAV Imagery

2. Vehicle Detection from Aerial Images Using Deep Learning: A Comparative Study

3. GPU-Based Embedded Intelligence Architectures and Applications

4. Improved single shot multibox detector target detection method based on deep feature fusion

5. Proposal for an Embedded System Architecture Using a GNDVI Algorithm to Support UAV-Based Agrochemical Spraying

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