Publications (18)
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…
Real-Time Pill Identification for the Visually Impaired Using Deep Learning
Bo Dang, Wenchao Zhao, Yufeng Li +3
The prevalence of mobile technology offers unique opportunities for addressing healthcare challenges, especially for individuals with visual impairments. This paper explores the de…
Research on Adverse Drug Reaction Prediction Model Combining Knowledge Graph Embedding and Deep Learning
Yufeng Li, Wenchao Zhao, Bo Dang +4
In clinical treatment, identifying potential adverse reactions of drugs can help assist doctors in making medication decisions. In response to the problems in previous studies that…
HoliTracer: Holistic Vectorization of Geographic Objects from Large-Size Remote Sensing Imagery
Yu Wang, Bo Dang, Wanchun Li +2
With the increasing resolution of remote sensing imagery (RSI), large-size RSI has emerged as a vital data source for high-precision vector mapping of geographic objects. Existing…
SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding
Junwei Luo, Zhen Pang, Yongjun Zhang +8
Remote Sensing Large Multi-Modal Models (RSLMMs) are developing rapidly and showcase significant capabilities in remote sensing imagery (RSI) comprehension. However, due to the lim…
Fostc3net:A Lightweight YOLOv5 Based On the Network Structure Optimization
Danqing Ma, Shaojie Li, Bo Dang +2
Transmission line detection technology is crucial for automatic monitoring and ensuring the safety of electrical facilities. The YOLOv5 series is currently one of the most advanced…
Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation
Bo Dang, Yansheng Li, Yongjun Zhang +1
Semi-supervised semantic segmentation focuses on the exploration of a small amount of labeled data and a large amount of unlabeled data, which is more in line with the demands of r…
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…
MEET: A Million-Scale Dataset for Fine-Grained Geospatial Scene Classification with Zoom-Free Remote Sensing Imagery
Yansheng Li, Yuning Wu, Gong Cheng +9
Accurate fine-grained geospatial scene classification using remote sensing imagery is essential for a wide range of applications. However, existing approaches often rely on manuall…
Utilizing the LightGBM Algorithm for Operator User Credit Assessment Research
Shaojie Li, Xinqi Dong, Danqing Ma +3
Mobile Internet user credit assessment is an important way for communication operators to establish decisions and formulate measures, and it is also a guarantee for operators to ob…
U2++ MoE: Scaling 4.7x parameters with minimal impact on RTF
Xingchen Song, Di Wu, Binbin Zhang +5
Scale has opened new frontiers in natural language processing, but at a high cost. In response, by learning to only activate a subset of parameters in training and inference, Mixtu…
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…
ZeroPrompt: Streaming Acoustic Encoders are Zero-Shot Masked LMs
Xingchen Song, Di Wu, Binbin Zhang +4
In this paper, we present ZeroPrompt (Figure 1-(a)) and the corresponding Prompt-and-Refine strategy (Figure 3), two simple but effective \textbf{training-free} methods to decrease…
Towards Privacy-preserved Pre-training of Remote Sensing Foundation Models with Federated Mutual-guidance Learning
Jieyi Tan, Chengwei Zhang, Bo Dang +1
Traditional Remote Sensing Foundation models (RSFMs) are pre-trained with a data-centralized paradigm, through self-supervision on large-scale curated remote sensing data. For each…
Leveraging Deep Learning and Xception Architecture for High-Accuracy MRI Classification in Alzheimer Diagnosis
Shaojie Li, Haichen Qu, Xinqi Dong +3
Exploring the application of deep learning technologies in the field of medical diagnostics, Magnetic Resonance Imaging (MRI) provides a unique perspective for observing and diagno…
STAR: A First-Ever Dataset and A Large-Scale Benchmark for Scene Graph Generation in Large-Size Satellite Imagery
Yansheng Li, Linlin Wang, Tingzhu Wang +11
Scene graph generation (SGG) in satellite imagery (SAI) benefits promoting understanding of geospatial scenarios from perception to cognition. In SAI, objects exhibit great variati…
Research on Brain Tumor Classification Method Based on Improved ResNet34 Network
Yufeng Li, Wenchao Zhao, Bo Dang +1
Previously, image interpretation in radiology relied heavily on manual methods. However, manual classification of brain tumor medical images is time-consuming and labor-intensive.…
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…