Deep Learning in Remote Sensing

被引：9

作者：

Zhu, Xiao Xiang ^{[1
,2
,3
,4
,5
,6
]}

Tuia, Devis ^{[7
,8
,9
,10
,11
]}

Mou, Lichao ^{[2
,6
,12
]}

Xia, Gui-Song ^{[13
,14
]}

Zhang, Liangpei ^{[15
]}

Xu, Feng ^{[16
,17
]}

Fraundorfer, Friedrich ^{[18
,19
,20
,21
,22
]}

机构：

[1] TUM, Signal Proc Earth Observat, Munich, Germany

[2] German Aerosp Ctr DLR, Cologne, Germany

[3] DLR, Remote Sensing Technol Inst, Team Signal Anal, Cologne, Germany

[4] Helmholtz Young Investigator Grp SiPEO, Munich, Germany

[5] DLR, Cologne, Germany

[6] TUM, Munich, Germany

[7] Univ Valencia, Valencia, Spain

[8] Univ Colorado, Boulder, CO 80309 USA

[9] Ecole Polytech Fed Lausanne, Lausanne, Switzerland

[10] Wageningen Univ, GeoInformat Sci & Remote Sensing Lab, Wageningen, Netherlands

[11] Univ Zurich, Zurich, Switzerland

[12] Univ Freiburg, Comp Vis Grp, Freiburg, Germany

[13] Wuhan Univ, Key Lab Informat Engn Surveying Mapping & Remote, Wuhan, Hubei, Peoples R China

[14] Paris Dauphine Univ, CNRS, Ctr Rech Math Decis, Paris, France

[15] Wuhan Univ, Wuhan, Hubei, Peoples R China

[16] Sch Informat Sci & Technol, Hefei, Anhui, Peoples R China

[17] Key Lab for Informat Sci Electromagnet Waves, Shanghai, Peoples R China

[18] Graz Univ Technol, Graz, Austria

[19] Univ Kentucky, Lexington, KY 40506 USA

[20] Univ N Carolina, Chapel Hill, NC USA

[21] Swiss Fed Inst Technol, Zurich, Switzerland

[22] Tech Univ Munich, Fac Civil Geo & Environm Engn, Munich, Germany

来源：

IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE | 2017年 / 5卷 / 04期

基金：

中国国家自然科学基金; 欧洲研究理事会; 瑞士国家科学基金会;

关键词：

CONVOLUTIONAL NEURAL-NETWORK; OBJECT DETECTION; HIGH-RESOLUTION; DATA-FUSION; SCENE CLASSIFICATION; VEHICLE DETECTION; IMAGE RETRIEVAL; SAR ATR; REPRESENTATION; FEATURES;

D O I：

10.1109/MGRS.2017.2762307

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

引用

页码：8 / 36

页数：29

共 50 条

[31] Spatiotemporal Fusion of Remote Sensing Image Based on Deep Learning
Wang, Xiaofei
Wang, Xiaoyi
JOURNAL OF SENSORS, 2020, 2020
[32] Special focus on deep learning in remote sensing image processing
Feng Xu
Cheng Hu
Jun Li
Antonio Plaza
Mihai Datcu
Science China Information Sciences, 2020, 63
[33] Survey of remote sensing image registration based on deep learning
Li X.
Ai W.
Feng R.
Luo S.
National Remote Sensing Bulletin, 2023, 27 (02) : 5 - 22
[34] The design of deep learning framework and model for intelligent remote sensing
Gong J.
Zhang M.
Hu X.
Zhang Z.
Li Y.
Jiang L.
Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2022, 51 (04): : 475 - 487
[35] A Deep Learning Hierarchical Ensemble for Remote Sensing Image Classification
Hwang, Seung-Yeon
Kim, Jeong-Joon
CMC-COMPUTERS MATERIALS & CONTINUA, 2022, 72 (02): : 2649 - 2663
[36] Research on remote sensing image extraction based on deep learning
Shun Z.
Li D.
Jiang H.
Li J.
Peng R.
Lin B.
Liu Q.
Gong X.
Zheng X.
Liu T.
PeerJ Computer Science, 2022, 8
[37] Classification of tobacco using remote sensing and deep learning techniques
Qazi, Umama Khalid
Ahmad, Iftikhar
Minallah, Nasru
Zeeshan, Muhammad
AGRONOMY JOURNAL, 2024, 116 (03) : 839 - 847
[38] Deep Learning in Damage Assessment with Remote Sensing Data: A Review
Irwansyah, Edy
Gunawan, Alexander Agung Santoso
DATA SCIENCE AND ALGORITHMS IN SYSTEMS, 2022, VOL 2, 2023, 597 : 728 - 739
[39] Introduction to the special issue on deep learning for remote sensing environments
Manogaran, Gunasekaran
Qudrat-Ullah, Hassan
Rawal Kshatriya, Bharat S.
EUROPEAN JOURNAL OF REMOTE SENSING, 2020, 53 (sup1) : 1 - 3
[40] Special focus on deep learning in remote sensing image processing
Xu, Feng
Hu, Cheng
Li, Jun
Plaza, Antonio
Datcu, Mihai
SCIENCE CHINA-INFORMATION SCIENCES, 2020, 63 (04)

← 1 2 3 4 5 →