Deep Learning and Machine Learning for Object Detection in Remote Sensing Images

Guowei Yang; Qiang Luo; Yinding Yang; Yin Zhuang

doi:10.1007/978-981-10-7521-6_30

Deep Learning and Machine Learning for Object Detection in Remote Sensing Images

Guowei Yang^*
, Qiang Luo
, Yinding Yang
, Yin Zhuang

^*Corresponding author for this work

School of Information and Electronics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Object detection is one of the most effective ways to analyze the remote sensing (RS) images. In this paper, we focus on the prevalent object detection framework based on deep learning technology for RS images which contains three different stages, namely the region proposals generation, feature extraction, and classification. The review provides a clear picture of the challenges and possible development trends in this field. Typical methods under this framework are extensively reviewed and analyzed. Comparisons among traditional methods with deep learning methods are presented, in which supervised and unsupervised methods for RS scene target detection are deeply discussed.

Original language	English
Title of host publication	Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC
Editors	Songlin Sun, Na Chen, Tao Tian
Publisher	Springer Verlag
Pages	249-256
Number of pages	8
ISBN (Print)	9789811075209
DOIs	https://doi.org/10.1007/978-981-10-7521-6_30
Publication status	Published - 2018
Event	3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2017 - Chongqing, China Duration: 13 Sept 2017 → 15 Sept 2017

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	473
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2017
Country/Territory	China
City	Chongqing
Period	13/09/17 → 15/09/17

Keywords

Deep learning
Object detection
Remote sensing

Access to Document

10.1007/978-981-10-7521-6_30

Cite this

Yang, G., Luo, Q., Yang, Y., & Zhuang, Y. (2018). Deep Learning and Machine Learning for Object Detection in Remote Sensing Images. In S. Sun, N. Chen, & T. Tian (Eds.), Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC (pp. 249-256). (Lecture Notes in Electrical Engineering; Vol. 473). Springer Verlag. https://doi.org/10.1007/978-981-10-7521-6_30

Yang, Guowei ; Luo, Qiang ; Yang, Yinding et al. / Deep Learning and Machine Learning for Object Detection in Remote Sensing Images. Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC. editor / Songlin Sun ; Na Chen ; Tao Tian. Springer Verlag, 2018. pp. 249-256 (Lecture Notes in Electrical Engineering).

@inproceedings{5e06f7e6d1ff4616b308e7c5de3f4b54,

title = "Deep Learning and Machine Learning for Object Detection in Remote Sensing Images",

abstract = "Object detection is one of the most effective ways to analyze the remote sensing (RS) images. In this paper, we focus on the prevalent object detection framework based on deep learning technology for RS images which contains three different stages, namely the region proposals generation, feature extraction, and classification. The review provides a clear picture of the challenges and possible development trends in this field. Typical methods under this framework are extensively reviewed and analyzed. Comparisons among traditional methods with deep learning methods are presented, in which supervised and unsupervised methods for RS scene target detection are deeply discussed.",

keywords = "Deep learning, Object detection, Remote sensing",

author = "Guowei Yang and Qiang Luo and Yinding Yang and Yin Zhuang",

note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Singapore Pte Ltd.; 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2017 ; Conference date: 13-09-2017 Through 15-09-2017",

year = "2018",

doi = "10.1007/978-981-10-7521-6\_30",

language = "English",

isbn = "9789811075209",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Verlag",

pages = "249--256",

editor = "Songlin Sun and Na Chen and Tao Tian",

booktitle = "Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC",

address = "Germany",

}

Yang, G, Luo, Q, Yang, Y & Zhuang, Y 2018, Deep Learning and Machine Learning for Object Detection in Remote Sensing Images. in S Sun, N Chen & T Tian (eds), Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC. Lecture Notes in Electrical Engineering, vol. 473, Springer Verlag, pp. 249-256, 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2017, Chongqing, China, 13/09/17. https://doi.org/10.1007/978-981-10-7521-6_30

Deep Learning and Machine Learning for Object Detection in Remote Sensing Images. / Yang, Guowei; Luo, Qiang; Yang, Yinding et al.
Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC. ed. / Songlin Sun; Na Chen; Tao Tian. Springer Verlag, 2018. p. 249-256 (Lecture Notes in Electrical Engineering; Vol. 473).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Deep Learning and Machine Learning for Object Detection in Remote Sensing Images

AU - Yang, Guowei

AU - Luo, Qiang

AU - Yang, Yinding

AU - Zhuang, Yin

PY - 2018

Y1 - 2018

N2 - Object detection is one of the most effective ways to analyze the remote sensing (RS) images. In this paper, we focus on the prevalent object detection framework based on deep learning technology for RS images which contains three different stages, namely the region proposals generation, feature extraction, and classification. The review provides a clear picture of the challenges and possible development trends in this field. Typical methods under this framework are extensively reviewed and analyzed. Comparisons among traditional methods with deep learning methods are presented, in which supervised and unsupervised methods for RS scene target detection are deeply discussed.

AB - Object detection is one of the most effective ways to analyze the remote sensing (RS) images. In this paper, we focus on the prevalent object detection framework based on deep learning technology for RS images which contains three different stages, namely the region proposals generation, feature extraction, and classification. The review provides a clear picture of the challenges and possible development trends in this field. Typical methods under this framework are extensively reviewed and analyzed. Comparisons among traditional methods with deep learning methods are presented, in which supervised and unsupervised methods for RS scene target detection are deeply discussed.

KW - Deep learning

KW - Object detection

KW - Remote sensing

UR - https://www.scopus.com/pages/publications/85040107034

U2 - 10.1007/978-981-10-7521-6_30

DO - 10.1007/978-981-10-7521-6_30

M3 - Conference contribution

AN - SCOPUS:85040107034

SN - 9789811075209

T3 - Lecture Notes in Electrical Engineering

SP - 249

EP - 256

BT - Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC

A2 - Sun, Songlin

A2 - Chen, Na

A2 - Tian, Tao

PB - Springer Verlag

T2 - 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC 2017

Y2 - 13 September 2017 through 15 September 2017

ER -

Yang G, Luo Q, Yang Y, Zhuang Y. Deep Learning and Machine Learning for Object Detection in Remote Sensing Images. In Sun S, Chen N, Tian T, editors, Signal and Information Processing, Networking and Computers - Proceedings of the 3rd International Conference on Signal and Information Processing, Networking and Computers, ICSINC. Springer Verlag. 2018. p. 249-256. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-10-7521-6_30

Deep Learning and Machine Learning for Object Detection in Remote Sensing Images

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