Loading [MathJax]/extensions/MathMenu.js

Congcong Duan - IEEE Xplore Author Profile

Scheduled Maintenance on Monday 1/13/2025

Single article sales and account management will be unavailable from 5:00 AM - 7:00 PM ET (09:00 - 23:00 UTC). We apologize for the inconvenience.

IEEE.org
IEEE Xplore
IEEE SA
IEEE Spectrum
More Sites

- Donate
- Personal Sign In

Institutional Sign In

Institutional Sign In

ADVANCED SEARCH

Author details

Congcong Duan

Publications

1

Citations

2

Publications by Year

20232023

Co-Authors:

Yong FengWeijia JiaBaohua QiangYongheng WangXiancai Xiong

Show All Co-Authors (6)

Congcong Duan

Affiliation

College of Computer Science

Chongqing University

Chongqing, China

Publication Topics

Batch Of Images,
Contrastive Loss,
Deep Learning,
Deep Metric Learning,
Deep Metrics,
Discriminative Features,
Dynamic Boundary,
Embedding Representation,
Geometric Information,
Global Distance,
Image Descriptors,
Image Retrieval

Biography

Congcong Duan received the bachelor's degree in computer science and technology from the School of Computer and Information Engineering, Henu University, Henan, China, in 2020. She is currently working toward the master's degree in computer science and technology from Chongqing University, Chongqing, China.,Her current research interests include deep metric learning, image retrieval, and deep learning.(Based on document published on 8 December 2022).

Publications

1

Citations

2

Publications by Year

20232023

Co-Authors:

Yong Feng
Weijia Jia
Baohua Qiang
Yongheng Wang
Xiancai Xiong

Show All Co-Authors (6)

Author's Published Works

Search History

Showing 1-5 of 5 results

Journals (5)

Sort

Filter Results

Show

Open Access Only

Range
Single Year
Zhenxuan Li(5)
Jun Geng(3)
Chunju Zhang(3)
Zhourun Ye(3)
Wenzhong Shi(2)
School of Civil Engineering, Hefei University of Technology, Hefei, China(2)
Intelligent Interconnected Systems Laboratory of Anhui Province, Hefei University of Technology, Hefei, China(2)
School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China(2)
College of Civil Engineering, Hefei University of Technology, Hefei, China(2)
Fujian Normal University, Fuzhou, China(1)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing(4)
IEEE Geoscience and Remote Sensing Letters(1)
IEEE(5)
Change Detection(2)
Change Detection Results(2)
Final Map(2)
Remote Sensing(2)
Remote Sensing Images(2)

Select All on Page

Sort By

Results

Subpixel Change Detection Based on Improved Abundance Values for Remote Sensing Images

Zhenxuan Li;Wenzhong Shi;Chunju Zhang;Jun Geng;Jianwei Huang;Zhourun Ye

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2022 | Volume: 15 | Journal Article |

Cited by: Papers (4)

HTML

To achieve land cover change detection (LCCD) with both fine spatial and temporal resolutions from remote sensing images, subpixel mapping-based approaches have been widely studied in recent years. The fine spatial but coarse temporal resolution image and the coarse spatial but fine temporal image are used to accomplish LCCD by combining their advantages. However, the performance of subpixel mappi...Show More

Subpixel Change Detection Based on Improved Abundance Values for Remote Sensing Images

Zhenxuan Li;Wenzhong Shi;Chunju Zhang;Jun Geng;Jianwei Huang;Zhourun Ye

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2022 | Volume: 15 | Journal Article |

Application of a Hypergeometric Model in Simulating Canopy Gap Fraction and BRF for Forest Plantations on Sloping Terrains

Jun Geng;Jing M. Chen;Weiliang Fan;Lili Tu;Yong Pang;Gang Yuan;Lichen Xu;Canyang Zhu;Teng Zhang;Chunju Zhang;Zhourun Ye;Yongchao Zhu;Zhenxuan Li

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2022 | Volume: 15 | Journal Article |

Cited by: Papers (10)

HTML

The influence of tree distribution and slope on canopy gap fraction (GF) and bidirectional reflectance factor (BRF) is shown here to be non-negligible. Trees are often assumed to be randomly distributed in natural forests due to random distribution of natural resources, but this assumption is not valid for forest plantations. A geometric optical model for forest plantations (GOFP) is a geometric o...Show More

Application of a Hypergeometric Model in Simulating Canopy Gap Fraction and BRF for Forest Plantations on Sloping Terrains

Jun Geng;Jing M. Chen;Weiliang Fan;Lili Tu;Yong Pang;Gang Yuan;Lichen Xu;Canyang Zhu;Teng Zhang;Chunju Zhang;Zhourun Ye;Yongchao Zhu;Zhenxuan Li

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2022 | Volume: 15 | Journal Article |

Hyperspectral Remote Sensing Image Classification Using Deep Convolutional Capsule Network

Runmin Lei;Chunju Zhang;Wencong Liu;Lei Zhang;Xueying Zhang;Yucheng Yang;Jianwei Huang;Zhenxuan Li;Zhiyi Zhou

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2021 | Volume: 14 | Journal Article |

Cited by: Papers (23)

HTML

Deep learning models have shown excellent performance in the hyperspectral remote sensing image (HSI) classification. In particular, convolutional neural networks (CNNs) have received widespread attention because of their powerful feature-extraction ability. Recently, a capsule network (CapsNet) was introduced to boost the performance of CNNs, marking a remarkable progress in the field of HSI clas...Show More

Hyperspectral Remote Sensing Image Classification Using Deep Convolutional Capsule Network

Runmin Lei;Chunju Zhang;Wencong Liu;Lei Zhang;Xueying Zhang;Yucheng Yang;Jianwei Huang;Zhenxuan Li;Zhiyi Zhou

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2021 | Volume: 14 | Journal Article |

Sensing Sea Ice Based on Doppler Spread Analysis of Spaceborne GNSS-R Data

Yongchao Zhu;Tingye Tao;Kegen Yu;Zhenxuan Li;Xiaochuan Qu;Zhourun Ye;Jun Geng;Jingui Zou;Maximilian Semmling;Jens Wickert

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2020 | Volume: 13 | Journal Article |

Cited by: Papers (29)

HTML

The spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) delay-Doppler map (DDM) data collected over ocean carry typical feature information about the ocean surface, which may be covered by open water, mixed water/ice, complete ice, etc. A new method based on Doppler spread analysis is proposed to remotely sense sea ice using the spaceborne GNSS-R data collected over the Northern a...Show More

Sensing Sea Ice Based on Doppler Spread Analysis of Spaceborne GNSS-R Data

Yongchao Zhu;Tingye Tao;Kegen Yu;Zhenxuan Li;Xiaochuan Qu;Zhourun Ye;Jun Geng;Jingui Zou;Maximilian Semmling;Jens Wickert

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Year: 2020 | Volume: 13 | Journal Article |

Change Detection Based on Gabor Wavelet Features for Very High Resolution Remote Sensing Images

Zhenxuan Li;Wenzhong Shi;Hua Zhang;Ming Hao

IEEE Geoscience and Remote Sensing Letters

Year: 2017 | Volume: 14, Issue: 5 | Journal Article |

Cited by: Papers (70)

HTML

In this letter, we propose a change detection method based on Gabor wavelet features for very high resolution (VHR) remote sensing images. First, Gabor wavelet features are extracted from two temporal VHR images to obtain spatial and contextual information. Then, the Gabor-wavelet-based difference measure (GWDM) is designed to generate the difference image. In GWDM, a new local similarity measure ...Show More

Change Detection Based on Gabor Wavelet Features for Very High Resolution Remote Sensing Images

Zhenxuan Li;Wenzhong Shi;Hua Zhang;Ming Hao

IEEE Geoscience and Remote Sensing Letters

Year: 2017 | Volume: 14, Issue: 5 | Journal Article |

IEEE Personal Account

Change username/password

Purchase Details

Payment Options
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

Follow

About IEEE Xplore | Contact Us | Help | Accessibility | Terms of Use | Nondiscrimination Policy | IEEE Ethics Reporting | Sitemap | IEEE Privacy Policy

A public charity, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

© Copyright 2025 IEEE - All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies.

IEEE Account

Change Username/Password
Update Address

Purchase Details

Payment Options
Order History
View Purchased Documents

Profile Information

Communications Preferences
Profession and Education
Technical Interests

Need Help?

US & Canada: +1 800 678 4333
Worldwide: +1 732 981 0060
Contact & Support

About IEEE Xplore
Contact Us
Help
Accessibility
Terms of Use
Nondiscrimination Policy
Sitemap
Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.

Test Whats new message.