65 citations · 87 across the 11 of their papers we have counts for
11 papers
FedEU: Evidential Uncertainty-Driven Federated Fine-Tuning of Vision Foundation Models for Remote Sensing Image Segmentation
Xiaokang Zhang, Xuran Xiong, Jianzhong Huang +1
Remote sensing image segmentation (RSIS) in federated environments has gained increasing attention because it enables collaborative model training across distributed datasets witho…
SIGMAE: A Spectral-Index-Guided Foundation Model for Multispectral Remote Sensing
Xiaokang Zhang, Bo Li, Chufeng Zhou +2
Pretraining and fine-tuning have emerged as a new paradigm in remote sensing image interpretation. Among them, Masked Autoencoder (MAE)-based pretraining stands out for its strong…
Kolmogorov-Arnold Network for Remote Sensing Image Semantic Segmentation
Xianping Ma, Ziyao Wang, Yin Hu +2
Semantic segmentation plays a crucial role in remote sensing applications, where the accurate extraction and representation of features are essential for high-quality results. Desp…
A Unified Framework with Multimodal Fine-tuning for Remote Sensing Semantic Segmentation
Xianping Ma, Xiaokang Zhang, Man-On Pun +1
Multimodal remote sensing data, acquired from diverse sensors, offer a comprehensive and integrated perspective of the Earth's surface. Leveraging multimodal fusion techniques, sem…
PyramidMamba: Rethinking Pyramid Feature Fusion with Selective Space State Model for Semantic Segmentation of Remote Sensing Imagery
Libo Wang, Dongxu Li, Sijun Dong +3
Semantic segmentation, as a basic tool for intelligent interpretation of remote sensing images, plays a vital role in many Earth Observation (EO) applications. Nowadays, accurate s…
RS3Mamba: Visual State Space Model for Remote Sensing Images Semantic Segmentation
Xianping Ma, Xiaokang Zhang, Man-On Pun
Semantic segmentation of remote sensing images is a fundamental task in geoscience research. However, there are some significant shortcomings for the widely used convolutional neur…
Decomposition-based Unsupervised Domain Adaptation for Remote Sensing Image Semantic Segmentation
Xianping Ma, Xiaokang Zhang, Xingchen Ding +2
Unsupervised domain adaptation (UDA) techniques are vital for semantic segmentation in geosciences, effectively utilizing remote sensing imagery across diverse domains. However, mo…
Adaptive Semantic-Enhanced Denoising Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution
Jialu Sui, Xianping Ma, Xiaokang Zhang +1
Remote sensing image super-resolution (SR) is a crucial task to restore high-resolution (HR) images from low-resolution (LR) observations. Recently, the Denoising Diffusion Probabi…
Diffusion Enhancement for Cloud Removal in Ultra-Resolution Remote Sensing Imagery
Jialu Sui, Yiyang Ma, Wenhan Yang +3
The presence of cloud layers severely compromises the quality and effectiveness of optical remote sensing (RS) images. However, existing deep-learning (DL)-based Cloud Removal (CR)…
SAM-Assisted Remote Sensing Imagery Semantic Segmentation with Object and Boundary Constraints
Xianping Ma, Qianqian Wu, Xingyu Zhao +3
Semantic segmentation of remote sensing imagery plays a pivotal role in extracting precise information for diverse down-stream applications. Recent development of the Segment Anyth…
GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPM
Yihan Wen, Xianping Ma, Xiaokang Zhang +1
Deep learning (DL)-based methods have recently shown great promise in bitemporal change detection (CD). Existing discriminative methods based on Convolutional Neural Networks (CNNs…