29 citations · 53 across the 9 of their papers we have counts for
10 papers
AUG: A New Dataset and An Efficient Model for Aerial Image Urban Scene Graph Generation
Yansheng Li, Kun Li, Yongjun Zhang +2
Scene graph generation (SGG) aims to understand the visual objects and their semantic relationships from one given image. Until now, lots of SGG datasets with the eyelevel view are…
Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation
Jieyi Tan, Yansheng Li, Sergey A. Bartalev +5
Remote sensing semantic segmentation (RSS) is an essential technology in earth observation missions. Due to concerns over geographic information security, data privacy, storage bot…
Learning to Holistically Detect Bridges from Large-Size VHR Remote Sensing Imagery
Yansheng Li, Junwei Luo, Yongjun Zhang +3
Bridge detection in remote sensing images (RSIs) plays a crucial role in various applications, but it poses unique challenges compared to the detection of other objects. In RSIs, b…
SkySense: A Multi-Modal Remote Sensing Foundation Model Towards Universal Interpretation for Earth Observation Imagery
Xin Guo, Jiangwei Lao, Bo Dang +13
Prior studies on Remote Sensing Foundation Model (RSFM) reveal immense potential towards a generic model for Earth Observation. Nevertheless, these works primarily focus on a singl…
GLH-Water: A Large-Scale Dataset for Global Surface Water Detection in Large-Size Very-High-Resolution Satellite Imagery
Yansheng Li, Bo Dang, Wanchun Li +1
Global surface water detection in very-high-resolution (VHR) satellite imagery can directly serve major applications such as refined flood mapping and water resource assessment. Al…
EHSNet: End-to-End Holistic Learning Network for Large-Size Remote Sensing Image Semantic Segmentation
Wei Chen, Yansheng Li, Bo Dang +1
This paper presents EHSNet, a new end-to-end segmentation network designed for the holistic learning of large-size remote sensing image semantic segmentation (LRISS). Large-size re…
Hierarchical Memory Learning for Fine-Grained Scene Graph Generation
Youming Deng, Yansheng Li, Yongjun Zhang +4
As far as Scene Graph Generation (SGG), coarse and fine predicates mix in the dataset due to the crowd-sourced labeling, and the long-tail problem is also pronounced. Given this tr…
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining
Ling Chen, Jun Cui, Xing Tang +4
Although the state-of-the-art traditional representation learning (TRL) models show competitive performance on knowledge graph completion, there is no parameter sharing between the…
Group-Aware Graph Neural Network for Nationwide City Air Quality Forecasting
Ling Chen, Jiahui Xu, Binqing Wu +4
The problem of air pollution threatens public health. Air quality forecasting can provide the air quality index hours or even days later, which can help the public to prevent air p…
Collaboratively boosting data-driven deep learning and knowledge-guided ontological reasoning for semantic segmentation of remote sensing imagery
Yansheng Li, Song Ouyang, Yongjun Zhang
As one kind of architecture from the deep learning family, deep semantic segmentation network (DSSN) achieves a certain degree of success on the semantic segmentation task and obvi…