1.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN6 papers
- Wuhan UniversityCN6 papers
- First Institute of OceanographyCN5 papers
- Ministry of Education of the People's Republic of ChinaCN5 papers
- Second Institute of OceanographyCN5 papers
- Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou)CN4 papers
- National University of Defense TechnologyCN3 papers
- South China University of TechnologyCN3 papers
- Dalian University of TechnologyCN2 papers
- Fujian Institute of OceanographyCN2 papers
- Guangzhou Marine Geological SurveyCN2 papers
- Hohai UniversityCN2 papers
10 papers · 1 filter
Weakly Supervised Cloud Detection Combining Spectral Features and Multi-Scale Deep Network
Shaocong Zhu, Zhiwei Li, Xinghua Li +1
Clouds significantly affect the quality of optical satellite images, which seriously limits their precise application. Recently, deep learning has been widely applied to cloud dete…
BD-MSA: Body decouple VHR Remote Sensing Image Change Detection method guided by multi-scale feature information aggregation
Yonghui Tan, Xiaolong Li, Yishu Chen +1
The purpose of remote sensing image change detection (RSCD) is to detect differences between bi-temporal images taken at the same place. Deep learning has been extensively used to…
MetaSegNet: Metadata-collaborative Vision-Language Representation Learning for Semantic Segmentation of Remote Sensing Images
Libo Wang, Sijun Dong, Ying Chen +3
Semantic segmentation of remote sensing images plays a vital role in a wide range of Earth Observation applications, such as land use land cover mapping, environment monitoring, an…
Exchanging Dual Encoder-Decoder: A New Strategy for Change Detection with Semantic Guidance and Spatial Localization
Sijie Zhao, Xueliang Zhang, Pengfeng Xiao +1
Change detection is a critical task in earth observation applications. Recently, deep learning-based methods have shown promising performance and are quickly adopted in change dete…
CMID: A Unified Self-Supervised Learning Framework for Remote Sensing Image Understanding
Dilxat Muhtar, Xueliang Zhang, Pengfeng Xiao +2
Self-supervised learning (SSL) has gained widespread attention in the remote sensing (RS) and earth observation (EO) communities owing to its ability to learn task-agnostic represe…
Building extraction with vision transformer
Libo Wang, Shenghui Fang, Rui Li +1
As an important carrier of human productive activities, the extraction of buildings is not only essential for urban dynamic monitoring but also necessary for suburban construction…
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
Libo Wang, Rui Li, Ce Zhang +4
Semantic segmentation of remotely sensed urban scene images is required in a wide range of practical applications, such as land cover mapping, urban change detection, environmental…
BDANet: Multiscale Convolutional Neural Network with Cross-directional Attention for Building Damage Assessment from Satellite Images
Yu Shen, Sijie Zhu, Taojiannan Yang +5
Fast and effective responses are required when a natural disaster (e.g., earthquake, hurricane, etc.) strikes. Building damage assessment from satellite imagery is critical before…
Efficient Deep Learning of Non-local Features for Hyperspectral Image Classification
Yu Shen, Sijie Zhu, Chen Chen +4
Deep learning based methods, such as Convolution Neural Network (CNN), have demonstrated their efficiency in hyperspectral image (HSI) classification. These methods can automatical…
Enhancing Remote Sensing Image Retrieval with Triplet Deep Metric Learning Network
Rui Cao, Qian Zhang, Jiasong Zhu +4
With the rapid growing of remotely sensed imagery data, there is a high demand for effective and efficient image retrieval tools to manage and exploit such data. In this letter, we…