23 citations · 34 across the 9 of their papers we have counts for
10 papers
Uncertainty-Aware Cross-Modal Remote Sensing Image-Text Retrieval via Evidential Learning
Zhuoyue Wang, Xueqian Wang, Gang Li +3
In cross-modal remote sensing image-text retrieval (CMRSITR), test-time remote sensing (RS) images and textual descriptions may deviate from well-curated benchmark conditions due t…
When marine radar target detection meets pretrained large language models
Qiying Hu, Linping Zhang, Xueqian Wang +3
Deep learning (DL) methods are widely used to extract high-dimensional patterns from the sequence features of radar echo signals. However, conventional DL algorithms face challenge…
A Novel Radar Constant False Alarm Rate Detection Algorithm Based on VAMP Deep Unfolding
Haoyun Zhang, Chengyang Zhang, Xueqian Wang +2
The combination of deep unfolding with vector approximate message passing (VAMP) algorithm, results in faster convergence and higher sparse recovery accuracy than traditional compr…
Parameter Convergence Radar Detector Based on VAMP Deep Unfolding
Haoyun Zhang, Jianghong Han, Xueqian Wang +2
Compared with the sparse recovery process in traditional compressed sensing (CS) radar detector CAMP, vector AMP deep unfolding (VAMP-DU) can achieve sparse recovery over a broader…
GLRT-Based Metric Learning for Remote Sensing Object Retrieval
Linping Zhang, Yu Liu, Xueqian Wang +2
With the improvement in the quantity and quality of remote sensing images, content-based remote sensing object retrieval (CBRSOR) has become an increasingly important topic. Howeve…
Lightweight Change Detection in Heterogeneous Remote Sensing Images with Online All-Integer Pruning Training
Chengyang Zhang, Weiming Li, Gang Li +4
Detection of changes in heterogeneous remote sensing images is vital, especially in response to emergencies like earthquakes and floods. Current homogenous transformation-based cha…
The Road to On-board Change Detection: A Lightweight Patch-Level Change Detection Network via Exploring the Potential of Pruning and Pooling
Lihui Xue, Zhihao Wang, Xueqian Wang +1
Existing satellite remote sensing change detection (CD) methods often crop original large-scale bi-temporal image pairs into small patch pairs and then use pixel-level CD methods t…
COMIC: An Unsupervised Change Detection Method for Heterogeneous Remote Sensing Images Based on Copula Mixtures and Cycle-Consistent Adversarial Networks
Chengxi Li, Gang Li, Zhuoyue Wang +2
In this paper, we consider the problem of change detection (CD) with two heterogeneous remote sensing (RS) images. For this problem, an unsupervised change detection method has bee…
NN-Copula-CD: A Copula-Guided Interpretable Neural Network for Change Detection in Heterogeneous Remote Sensing Images
Weiming Li, Xueqian Wang, Gang Li +2
Change detection (CD) in heterogeneous remote sensing images has been widely used for disaster monitoring and land-use management. In the past decade, the heterogeneous CD problem…
MCTNet: A Multi-Scale CNN-Transformer Network for Change Detection in Optical Remote Sensing Images
Weiming Li, Lihui Xue, Xueqian Wang +1
For the task of change detection (CD) in remote sensing images, deep convolution neural networks (CNNs)-based methods have recently aggregated transformer modules to improve the ca…