Vehicle Detection under UAV Based on Optimal Dense YOLO Method

Zhi Xu, Haochen Shi, Ning Li*, Chao Xiang, Huiyu Zhou

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

In this paper, a deep neural network model based on small target detection under UAV platform is designed. Due to the One-stage detection model like YOLO having novel structure and great industrial application potential, this paper proposes a new model of detection based on YOLOv2 structure. Faced with missed detection problem of small target, a series of improved schemes are proposed, which are suitable for small vehicles' detection under aerial view angle, and can achieve real-time detection, including dense topology and optimal pooling strategy.

Original languageEnglish
Title of host publication2018 5th International Conference on Systems and Informatics (ICSAI 2018): Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages407-411
Number of pages5
ISBN (Electronic)9781728101200
ISBN (Print)978-1-7281-0121-7
DOIs
Publication statusPublished - 03 Jan 2019
Externally publishedYes
Event5th International Conference on Systems and Informatics, ICSAI 2018 - Nanjing, China
Duration: 10 Nov 201812 Nov 2018

Publication series

Name2018 5th International Conference on Systems and Informatics, ICSAI 2018

Conference

Conference5th International Conference on Systems and Informatics, ICSAI 2018
CountryChina
CityNanjing
Period10/11/201812/11/2018

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work received support from Science and Technology on Electro-optic Control Laboratory and Aviation Science Foundation Project (No 20175152036). The authors are also grateful for the support of their colleagues at the Key Laboratory of Radar Imaging and Microwave Photonics, Ministry of Education.

Publisher Copyright:
© 2018 IEEE.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

Keywords

  • deep learning
  • UAV
  • vehicle detection
  • YOLO

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Energy Engineering and Power Technology
  • Control and Systems Engineering

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